Projects/step_5/2.statictics intermediate/Guided Project_Finding the Best Markets to Advertise In.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Finding the Best Two Markets to Advertise In"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this project, we'll aim to find the two best markets to advertise our product in — we're working for an e-learning company that offers courses on programming. Most of our courses are on web and mobile development, but we also cover many other domains, like data science, game development, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Understanding the Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To avoid spending money on organizing a survey, we'll first try to make use of existing data to determine whether we can reach any reliable result.\n",
    "\n",
    "One good candidate for our purpose is [freeCodeCamp's 2017 New Coder Survey](https://medium.freecodecamp.org/we-asked-20-000-people-who-they-are-and-how-theyre-learning-to-code-fff5d668969). [freeCodeCamp](https://www.freecodecamp.org/) is a free e-learning platform that offers courses on web development. Because they run a popular [Medium publication](https://medium.freecodecamp.org/) (over 400,000 followers), their survey attracted new coders with varying interests (not only web development), which is ideal for the purpose of our analysis.\n",
    "\n",
    "The survey data is publicly available in this [GitHub repository](https://github.com/freeCodeCamp/2017-new-coder-survey). Below, we'll do a quick exploration of the 2017-fCC-New-Coders-Survey-Data.csv file stored in the clean-data folder of the repository we just mentioned. We'll read in the file using the direct link [here](https://raw.githubusercontent.com/freeCodeCamp/2017-new-coder-survey/master/clean-data/2017-fCC-New-Coders-Survey-Data.csv)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(18175, 136)\n"
     ]
    },
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       "      <th>JobInterestQAEngr</th>\n",
       "      <th>JobInterestUX</th>\n",
       "      <th>JobPref</th>\n",
       "      <th>JobRelocateYesNo</th>\n",
       "      <th>JobRoleInterest</th>\n",
       "      <th>JobWherePref</th>\n",
       "      <th>LanguageAtHome</th>\n",
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       "      <th>MoneyForLearning</th>\n",
       "      <th>MonthsProgramming</th>\n",
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       "      <th>Part1EndTime</th>\n",
       "      <th>Part1StartTime</th>\n",
       "      <th>Part2EndTime</th>\n",
       "      <th>Part2StartTime</th>\n",
       "      <th>PodcastChangeLog</th>\n",
       "      <th>PodcastCodeNewbie</th>\n",
       "      <th>PodcastCodePen</th>\n",
       "      <th>PodcastDevTea</th>\n",
       "      <th>PodcastDotNET</th>\n",
       "      <th>PodcastGiantRobots</th>\n",
       "      <th>PodcastJSAir</th>\n",
       "      <th>PodcastJSJabber</th>\n",
       "      <th>PodcastNone</th>\n",
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       "      <th>PodcastProgThrowdown</th>\n",
       "      <th>PodcastRubyRogues</th>\n",
       "      <th>PodcastSEDaily</th>\n",
       "      <th>PodcastSERadio</th>\n",
       "      <th>PodcastShopTalk</th>\n",
       "      <th>PodcastTalkPython</th>\n",
       "      <th>PodcastTheWebAhead</th>\n",
       "      <th>ResourceCodecademy</th>\n",
       "      <th>ResourceCodeWars</th>\n",
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       "      <th>ResourceUdacity</th>\n",
       "      <th>ResourceUdemy</th>\n",
       "      <th>ResourceW3S</th>\n",
       "      <th>SchoolDegree</th>\n",
       "      <th>SchoolMajor</th>\n",
       "      <th>StudentDebtOwe</th>\n",
       "      <th>YouTubeCodeCourse</th>\n",
       "      <th>YouTubeCodingTrain</th>\n",
       "      <th>YouTubeCodingTut360</th>\n",
       "      <th>YouTubeComputerphile</th>\n",
       "      <th>YouTubeDerekBanas</th>\n",
       "      <th>YouTubeDevTips</th>\n",
       "      <th>YouTubeEngineeredTruth</th>\n",
       "      <th>YouTubeFCC</th>\n",
       "      <th>YouTubeFunFunFunction</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>15 to 29 minutes</td>\n",
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       "      <td>software development and IT</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>female</td>\n",
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       "      <td>02d9465b21e8bd09374b0066fb2d5614</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>English</td>\n",
       "      <td>married or domestic partnership</td>\n",
       "      <td>150.0</td>\n",
       "      <td>6.0</td>\n",
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       "      <td>2017-03-09 00:36:22</td>\n",
       "      <td>2017-03-09 00:32:59</td>\n",
       "      <td>2017-03-09 00:59:46</td>\n",
       "      <td>2017-03-09 00:36:26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>34.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>less than 100,000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not working but looking for work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35000.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
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       "      <td>1.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>10.0</td>\n",
       "      <td>5bfef9ecb211ec4f518cfc1d2a6f3e0c</td>\n",
       "      <td>21db37adb60cdcafadfa7dca1b13b6b1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Within 7 to 12 months</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a nonprofit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Full-Stack Web Developer</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>English</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>80.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>f8f8be6910</td>\n",
       "      <td>2017-03-09 00:37:07</td>\n",
       "      <td>2017-03-09 00:33:26</td>\n",
       "      <td>2017-03-09 00:38:59</td>\n",
       "      <td>2017-03-09 00:37:10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>some college credit, no degree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15 to 29 minutes</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>software development and IT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.0</td>\n",
       "      <td>14f1863afa9c7de488050b82eb3edd96</td>\n",
       "      <td>21ba173828fbe9e27ccebaf4d5166a55</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Within 7 to 12 months</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a medium-sized company</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Front-End Web Developer, Back-End Web Develo...</td>\n",
       "      <td>no preference</td>\n",
       "      <td>Spanish</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2ed189768e</td>\n",
       "      <td>2017-03-09 00:37:58</td>\n",
       "      <td>2017-03-09 00:33:53</td>\n",
       "      <td>2017-03-09 00:40:14</td>\n",
       "      <td>2017-03-09 00:38:02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Codenewbie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>high school diploma or equivalent (GED)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>between 100,000 and 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>I work from home</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>software development and IT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>91756eb4dc280062a541c25a3d44cfb0</td>\n",
       "      <td>3be37b558f02daae93a6da10f83f0c77</td>\n",
       "      <td>24000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Within the next 6 months</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a medium-sized company</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Front-End Web Developer, Full-Stack Web Deve...</td>\n",
       "      <td>from home</td>\n",
       "      <td>Portuguese</td>\n",
       "      <td>married or domestic partnership</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>dbdc0664d1</td>\n",
       "      <td>2017-03-09 00:40:13</td>\n",
       "      <td>2017-03-09 00:37:45</td>\n",
       "      <td>2017-03-09 00:42:26</td>\n",
       "      <td>2017-03-09 00:40:18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>some college credit, no degree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>between 100,000 and 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not working but looking for work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>aa3f061a1949a90b27bef7411ecd193f</td>\n",
       "      <td>d7c56bbf2c7b62096be9db010e86d96d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Within 7 to 12 months</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a multinational corporation</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Full-Stack Web Developer, Information Security...</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>Portuguese</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>11b0f2d8a9</td>\n",
       "      <td>2017-03-09 00:42:45</td>\n",
       "      <td>2017-03-09 00:39:44</td>\n",
       "      <td>2017-03-09 00:45:42</td>\n",
       "      <td>2017-03-09 00:42:50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Age  AttendedBootcamp  BootcampFinish  BootcampLoanYesNo BootcampName  \\\n",
       "0  27.0               0.0             NaN                NaN          NaN   \n",
       "1  34.0               0.0             NaN                NaN          NaN   \n",
       "2  21.0               0.0             NaN                NaN          NaN   \n",
       "3  26.0               0.0             NaN                NaN          NaN   \n",
       "4  20.0               0.0             NaN                NaN          NaN   \n",
       "\n",
       "   BootcampRecommend  ChildrenNumber                 CityPopulation  \\\n",
       "0                NaN             NaN            more than 1 million   \n",
       "1                NaN             NaN              less than 100,000   \n",
       "2                NaN             NaN            more than 1 million   \n",
       "3                NaN             NaN  between 100,000 and 1 million   \n",
       "4                NaN             NaN  between 100,000 and 1 million   \n",
       "\n",
       "   CodeEventConferences  CodeEventDjangoGirls  CodeEventFCC  CodeEventGameJam  \\\n",
       "0                   NaN                   NaN           NaN               NaN   \n",
       "1                   NaN                   NaN           NaN               NaN   \n",
       "2                   NaN                   NaN           NaN               NaN   \n",
       "3                   NaN                   NaN           NaN               NaN   \n",
       "4                   NaN                   NaN           NaN               NaN   \n",
       "\n",
       "   CodeEventGirlDev  CodeEventHackathons  CodeEventMeetup  \\\n",
       "0               NaN                  NaN              NaN   \n",
       "1               NaN                  NaN              NaN   \n",
       "2               NaN                  1.0              NaN   \n",
       "3               NaN                  NaN              NaN   \n",
       "4               NaN                  NaN              NaN   \n",
       "\n",
       "   CodeEventNodeSchool  CodeEventNone CodeEventOther  CodeEventRailsBridge  \\\n",
       "0                  NaN            NaN            NaN                   NaN   \n",
       "1                  NaN            NaN            NaN                   NaN   \n",
       "2                  1.0            NaN            NaN                   NaN   \n",
       "3                  NaN            NaN            NaN                   NaN   \n",
       "4                  NaN            NaN            NaN                   NaN   \n",
       "\n",
       "   CodeEventRailsGirls  CodeEventStartUpWknd  CodeEventWkdBootcamps  \\\n",
       "0                  NaN                   NaN                    NaN   \n",
       "1                  NaN                   NaN                    NaN   \n",
       "2                  NaN                   NaN                    NaN   \n",
       "3                  NaN                   NaN                    NaN   \n",
       "4                  NaN                   NaN                    NaN   \n",
       "\n",
       "   CodeEventWomenCode  CodeEventWorkshops       CommuteTime  \\\n",
       "0                 NaN                 NaN  15 to 29 minutes   \n",
       "1                 NaN                 NaN               NaN   \n",
       "2                 NaN                 NaN  15 to 29 minutes   \n",
       "3                 NaN                 NaN  I work from home   \n",
       "4                 NaN                 NaN               NaN   \n",
       "\n",
       "             CountryCitizen               CountryLive  \\\n",
       "0                    Canada                    Canada   \n",
       "1  United States of America  United States of America   \n",
       "2  United States of America  United States of America   \n",
       "3                    Brazil                    Brazil   \n",
       "4                  Portugal                  Portugal   \n",
       "\n",
       "               EmploymentField EmploymentFieldOther  \\\n",
       "0  software development and IT                  NaN   \n",
       "1                          NaN                  NaN   \n",
       "2  software development and IT                  NaN   \n",
       "3  software development and IT                  NaN   \n",
       "4                          NaN                  NaN   \n",
       "\n",
       "                   EmploymentStatus EmploymentStatusOther  ExpectedEarning  \\\n",
       "0                Employed for wages                   NaN              NaN   \n",
       "1  Not working but looking for work                   NaN          35000.0   \n",
       "2                Employed for wages                   NaN          70000.0   \n",
       "3                Employed for wages                   NaN          40000.0   \n",
       "4  Not working but looking for work                   NaN         140000.0   \n",
       "\n",
       "   FinanciallySupporting  FirstDevJob  Gender GenderOther  HasChildren  \\\n",
       "0                    NaN          NaN  female         NaN          NaN   \n",
       "1                    NaN          NaN    male         NaN          NaN   \n",
       "2                    NaN          NaN    male         NaN          NaN   \n",
       "3                    0.0          NaN    male         NaN          0.0   \n",
       "4                    NaN          NaN  female         NaN          NaN   \n",
       "\n",
       "   HasDebt  HasFinancialDependents  HasHighSpdInternet  HasHomeMortgage  \\\n",
       "0      1.0                     0.0                 1.0              0.0   \n",
       "1      1.0                     0.0                 1.0              0.0   \n",
       "2      0.0                     0.0                 1.0              NaN   \n",
       "3      1.0                     1.0                 1.0              1.0   \n",
       "4      0.0                     0.0                 1.0              NaN   \n",
       "\n",
       "   HasServedInMilitary  HasStudentDebt  HomeMortgageOwe  HoursLearning  \\\n",
       "0                  0.0             0.0              NaN           15.0   \n",
       "1                  0.0             1.0              NaN           10.0   \n",
       "2                  0.0             NaN              NaN           25.0   \n",
       "3                  0.0             0.0          40000.0           14.0   \n",
       "4                  0.0             NaN              NaN           10.0   \n",
       "\n",
       "                               ID.x                              ID.y  \\\n",
       "0  02d9465b21e8bd09374b0066fb2d5614  eb78c1c3ac6cd9052aec557065070fbf   \n",
       "1  5bfef9ecb211ec4f518cfc1d2a6f3e0c  21db37adb60cdcafadfa7dca1b13b6b1   \n",
       "2  14f1863afa9c7de488050b82eb3edd96  21ba173828fbe9e27ccebaf4d5166a55   \n",
       "3  91756eb4dc280062a541c25a3d44cfb0  3be37b558f02daae93a6da10f83f0c77   \n",
       "4  aa3f061a1949a90b27bef7411ecd193f  d7c56bbf2c7b62096be9db010e86d96d   \n",
       "\n",
       "    Income  IsEthnicMinority  IsReceiveDisabilitiesBenefits  IsSoftwareDev  \\\n",
       "0      NaN               NaN                            0.0            0.0   \n",
       "1      NaN               0.0                            0.0            0.0   \n",
       "2  13000.0               1.0                            0.0            0.0   \n",
       "3  24000.0               0.0                            0.0            0.0   \n",
       "4      NaN               0.0                            0.0            0.0   \n",
       "\n",
       "   IsUnderEmployed              JobApplyWhen  JobInterestBackEnd  \\\n",
       "0              0.0                       NaN                 NaN   \n",
       "1              NaN     Within 7 to 12 months                 NaN   \n",
       "2              0.0     Within 7 to 12 months                 1.0   \n",
       "3              1.0  Within the next 6 months                 1.0   \n",
       "4              NaN     Within 7 to 12 months                 1.0   \n",
       "\n",
       "   JobInterestDataEngr  JobInterestDataSci  JobInterestDevOps  \\\n",
       "0                  NaN                 NaN                NaN   \n",
       "1                  NaN                 NaN                NaN   \n",
       "2                  NaN                 NaN                1.0   \n",
       "3                  NaN                 NaN                NaN   \n",
       "4                  NaN                 NaN                NaN   \n",
       "\n",
       "   JobInterestFrontEnd  JobInterestFullStack  JobInterestGameDev  \\\n",
       "0                  NaN                   NaN                 NaN   \n",
       "1                  NaN                   1.0                 NaN   \n",
       "2                  1.0                   1.0                 NaN   \n",
       "3                  1.0                   1.0                 NaN   \n",
       "4                  1.0                   1.0                 NaN   \n",
       "\n",
       "   JobInterestInfoSec  JobInterestMobile JobInterestOther  \\\n",
       "0                 NaN                NaN              NaN   \n",
       "1                 NaN                NaN              NaN   \n",
       "2                 NaN                1.0              NaN   \n",
       "3                 NaN                NaN              NaN   \n",
       "4                 1.0                1.0              NaN   \n",
       "\n",
       "   JobInterestProjMngr  JobInterestQAEngr  JobInterestUX  \\\n",
       "0                  NaN                NaN            NaN   \n",
       "1                  NaN                NaN            NaN   \n",
       "2                  NaN                NaN            NaN   \n",
       "3                  NaN                NaN            NaN   \n",
       "4                  NaN                NaN            NaN   \n",
       "\n",
       "                                JobPref  JobRelocateYesNo  \\\n",
       "0               start your own business               NaN   \n",
       "1                  work for a nonprofit               1.0   \n",
       "2       work for a medium-sized company               1.0   \n",
       "3       work for a medium-sized company               NaN   \n",
       "4  work for a multinational corporation               1.0   \n",
       "\n",
       "                                     JobRoleInterest  \\\n",
       "0                                                NaN   \n",
       "1                           Full-Stack Web Developer   \n",
       "2    Front-End Web Developer, Back-End Web Develo...   \n",
       "3    Front-End Web Developer, Full-Stack Web Deve...   \n",
       "4  Full-Stack Web Developer, Information Security...   \n",
       "\n",
       "                         JobWherePref LanguageAtHome  \\\n",
       "0                                 NaN        English   \n",
       "1  in an office with other developers        English   \n",
       "2                       no preference        Spanish   \n",
       "3                           from home     Portuguese   \n",
       "4  in an office with other developers     Portuguese   \n",
       "\n",
       "                     MaritalStatus  MoneyForLearning  MonthsProgramming  \\\n",
       "0  married or domestic partnership             150.0                6.0   \n",
       "1            single, never married              80.0                6.0   \n",
       "2            single, never married            1000.0                5.0   \n",
       "3  married or domestic partnership               0.0                5.0   \n",
       "4            single, never married               0.0               24.0   \n",
       "\n",
       "    NetworkID         Part1EndTime       Part1StartTime         Part2EndTime  \\\n",
       "0  6f1fbc6b2b  2017-03-09 00:36:22  2017-03-09 00:32:59  2017-03-09 00:59:46   \n",
       "1  f8f8be6910  2017-03-09 00:37:07  2017-03-09 00:33:26  2017-03-09 00:38:59   \n",
       "2  2ed189768e  2017-03-09 00:37:58  2017-03-09 00:33:53  2017-03-09 00:40:14   \n",
       "3  dbdc0664d1  2017-03-09 00:40:13  2017-03-09 00:37:45  2017-03-09 00:42:26   \n",
       "4  11b0f2d8a9  2017-03-09 00:42:45  2017-03-09 00:39:44  2017-03-09 00:45:42   \n",
       "\n",
       "        Part2StartTime  PodcastChangeLog  PodcastCodeNewbie  PodcastCodePen  \\\n",
       "0  2017-03-09 00:36:26               NaN                NaN             NaN   \n",
       "1  2017-03-09 00:37:10               NaN                1.0             NaN   \n",
       "2  2017-03-09 00:38:02               1.0                NaN             1.0   \n",
       "3  2017-03-09 00:40:18               NaN                NaN             NaN   \n",
       "4  2017-03-09 00:42:50               NaN                NaN             NaN   \n",
       "\n",
       "   PodcastDevTea  PodcastDotNET  PodcastGiantRobots  PodcastJSAir  \\\n",
       "0            1.0            NaN                 NaN           NaN   \n",
       "1            NaN            NaN                 NaN           NaN   \n",
       "2            NaN            NaN                 NaN           NaN   \n",
       "3            NaN            NaN                 NaN           NaN   \n",
       "4            NaN            NaN                 NaN           NaN   \n",
       "\n",
       "   PodcastJSJabber  PodcastNone PodcastOther  PodcastProgThrowdown  \\\n",
       "0              NaN          NaN          NaN                   NaN   \n",
       "1              NaN          NaN          NaN                   NaN   \n",
       "2              NaN          NaN   Codenewbie                   NaN   \n",
       "3              NaN          NaN          NaN                   NaN   \n",
       "4              NaN          NaN          NaN                   NaN   \n",
       "\n",
       "   PodcastRubyRogues  PodcastSEDaily  PodcastSERadio  PodcastShopTalk  \\\n",
       "0                NaN             NaN             NaN              NaN   \n",
       "1                NaN             NaN             NaN              NaN   \n",
       "2                NaN             NaN             NaN              1.0   \n",
       "3                NaN             NaN             NaN              NaN   \n",
       "4                NaN             NaN             NaN              NaN   \n",
       "\n",
       "   PodcastTalkPython  PodcastTheWebAhead  ResourceCodecademy  \\\n",
       "0                NaN                 NaN                 1.0   \n",
       "1                NaN                 NaN                 1.0   \n",
       "2                NaN                 NaN                 1.0   \n",
       "3                NaN                 NaN                 NaN   \n",
       "4                NaN                 NaN                 NaN   \n",
       "\n",
       "   ResourceCodeWars  ResourceCoursera  ResourceCSS  ResourceEdX  \\\n",
       "0               NaN               NaN          NaN          NaN   \n",
       "1               NaN               NaN          1.0          NaN   \n",
       "2               NaN               NaN          1.0          NaN   \n",
       "3               NaN               NaN          NaN          NaN   \n",
       "4               NaN               NaN          NaN          NaN   \n",
       "\n",
       "   ResourceEgghead  ResourceFCC  ResourceHackerRank  ResourceKA  \\\n",
       "0              NaN          1.0                 NaN         NaN   \n",
       "1              NaN          1.0                 NaN         NaN   \n",
       "2              NaN          1.0                 NaN         NaN   \n",
       "3              1.0          1.0                 NaN         NaN   \n",
       "4              NaN          NaN                 NaN         NaN   \n",
       "\n",
       "   ResourceLynda  ResourceMDN  ResourceOdinProj ResourceOther  \\\n",
       "0            NaN          1.0               NaN           NaN   \n",
       "1            NaN          NaN               NaN           NaN   \n",
       "2            NaN          1.0               NaN           NaN   \n",
       "3            NaN          1.0               NaN           NaN   \n",
       "4            NaN          NaN               NaN           NaN   \n",
       "\n",
       "   ResourcePluralSight  ResourceSkillcrush  ResourceSO  ResourceTreehouse  \\\n",
       "0                  NaN                 NaN         NaN                NaN   \n",
       "1                  NaN                 NaN         1.0                NaN   \n",
       "2                  NaN                 NaN         NaN                NaN   \n",
       "3                  NaN                 NaN         1.0                NaN   \n",
       "4                  NaN                 NaN         1.0                NaN   \n",
       "\n",
       "   ResourceUdacity  ResourceUdemy  ResourceW3S  \\\n",
       "0              NaN            1.0          1.0   \n",
       "1              NaN            1.0          1.0   \n",
       "2              1.0            1.0          NaN   \n",
       "3              NaN            NaN          NaN   \n",
       "4              NaN            NaN          NaN   \n",
       "\n",
       "                              SchoolDegree             SchoolMajor  \\\n",
       "0           some college credit, no degree                     NaN   \n",
       "1           some college credit, no degree                     NaN   \n",
       "2  high school diploma or equivalent (GED)                     NaN   \n",
       "3           some college credit, no degree                     NaN   \n",
       "4                        bachelor's degree  Information Technology   \n",
       "\n",
       "   StudentDebtOwe  YouTubeCodeCourse  YouTubeCodingTrain  YouTubeCodingTut360  \\\n",
       "0             NaN                NaN                 NaN                  NaN   \n",
       "1             NaN                NaN                 NaN                  NaN   \n",
       "2             NaN                NaN                 NaN                  1.0   \n",
       "3             NaN                NaN                 NaN                  NaN   \n",
       "4             NaN                NaN                 NaN                  NaN   \n",
       "\n",
       "   YouTubeComputerphile  YouTubeDerekBanas  YouTubeDevTips  \\\n",
       "0                   NaN                NaN             NaN   \n",
       "1                   NaN                NaN             NaN   \n",
       "2                   NaN                1.0             1.0   \n",
       "3                   NaN                NaN             1.0   \n",
       "4                   NaN                NaN             NaN   \n",
       "\n",
       "   YouTubeEngineeredTruth  YouTubeFCC  YouTubeFunFunFunction  \\\n",
       "0                     NaN         NaN                    NaN   \n",
       "1                     NaN         1.0                    NaN   \n",
       "2                     NaN         NaN                    NaN   \n",
       "3                     NaN         1.0                    1.0   \n",
       "4                     NaN         NaN                    NaN   \n",
       "\n",
       "   YouTubeGoogleDev  YouTubeLearnCode  YouTubeLevelUpTuts  YouTubeMIT  \\\n",
       "0               NaN               NaN                 NaN         NaN   \n",
       "1               NaN               NaN                 NaN         NaN   \n",
       "2               NaN               1.0                 1.0         NaN   \n",
       "3               NaN               NaN                 1.0         NaN   \n",
       "4               NaN               NaN                 NaN         NaN   \n",
       "\n",
       "   YouTubeMozillaHacks YouTubeOther  YouTubeSimplilearn  YouTubeTheNewBoston  \n",
       "0                  NaN          NaN                 NaN                  NaN  \n",
       "1                  NaN          NaN                 NaN                  NaN  \n",
       "2                  NaN          NaN                 NaN                  NaN  \n",
       "3                  NaN          NaN                 NaN                  NaN  \n",
       "4                  NaN          NaN                 NaN                  NaN  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read in the data\n",
    "import pandas as pd\n",
    "direct_link = 'https://raw.githubusercontent.com/freeCodeCamp/2017-new-coder-survey/master/clean-data/2017-fCC-New-Coders-Survey-Data.csv'\n",
    "fcc = pd.read_csv(direct_link, low_memory = 0) # low_memory = False to silence dtypes warning\n",
    "\n",
    "# Quick exploration of the data\n",
    "print(fcc.shape)\n",
    "pd.options.display.max_columns = 150 # to avoid truncated output \n",
    "fcc.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Checking for Sample Representativity\n",
    "\n",
    "As we mentioned in the introduction, most of our courses are on web and mobile development, but we also cover many other domains, like data science, game development, etc. For the purpose of our analysis, we want to answer questions about a population of new coders that are interested in the subjects we teach. We'd like to know:\n",
    "\n",
    "Where are these new coders located.\n",
    "What locations have the greatest densities of new coders.\n",
    "How much money they're willing to spend on learning.\n",
    "So we first need to clarify whether the data set has the right categories of people for our purpose. The JobRoleInterest column describes for every participant the role(s) they'd be interested in working in. If a participant is interested in working in a certain domain, it means that they're also interested in learning about that domain. So let's take a look at the frequency distribution table of this column and determine whether the data we have is relevant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Full-Stack Web Developer                                                                                                                       11.770595\n",
       "  Front-End Web Developer                                                                                                                       6.435927\n",
       "  Data Scientist                                                                                                                                2.173913\n",
       "Back-End Web Developer                                                                                                                          2.030892\n",
       "  Mobile Developer                                                                                                                              1.673341\n",
       "                                                                                                                                                 ...    \n",
       "Desktop Applications Programmer                                                                                                                 0.014302\n",
       "Back-End Web Developer, Game Developer,   Mobile Developer, Full-Stack Web Developer,   Front-End Web Developer,   User Experience Designer     0.014302\n",
       "  Mobile Developer,   User Experience Designer,   Data Scientist, Information Security,   Front-End Web Developer, Game Developer               0.014302\n",
       "Network                                                                                                                                         0.014302\n",
       "  Front-End Web Developer, Full-Stack Web Developer,   Data Scientist, Back-End Web Developer,   Mobile Developer                               0.014302\n",
       "Name: JobRoleInterest, Length: 3213, dtype: float64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Frequency distribution table for 'JobRoleInterest'\n",
    "fcc['JobRoleInterest'].value_counts(normalize = True) * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "The information in the table above is quite granular, but from a quick scan it looks like:\n",
    "\n",
    "* A lot of people are interested in web development (full-stack web development, front-end web development and back-end web development).\n",
    "* A few people are interested in mobile development.\n",
    "* A few people are interested in domains other than web and mobile development.\n",
    "\n",
    "It's also interesting to note that many respondents are interested in more than one subject. It'd be useful to get a better picture of how many people are interested in a single subject and how many have mixed interests. Consequently, in the next code block, we'll:\n",
    "\n",
    "* Split each string in the JobRoleInterest column to find the number of options for each participant.\n",
    "   * We'll first drop the null values because we can't split Nan values.\n",
    "* Generate a frequency table for the variable describing the number of options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1     31.650458\n",
       "2     10.883867\n",
       "3     15.889588\n",
       "4     15.217391\n",
       "5     12.042334\n",
       "6      6.721968\n",
       "7      3.861556\n",
       "8      1.759153\n",
       "9      0.986842\n",
       "10     0.471968\n",
       "11     0.185927\n",
       "12     0.300343\n",
       "13     0.028604\n",
       "Name: JobRoleInterest, dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Split each string in the 'JobRoleInterest' column\n",
    "interests_no_nulls = fcc['JobRoleInterest'].dropna()\n",
    "splitted_interests = interests_no_nulls.str.split(',')\n",
    "\n",
    "# Frequency table for the var describing the number of options\n",
    "n_of_options = splitted_interests.apply(lambda x: len(x)) # x is a list of job options\n",
    "n_of_options.value_counts(normalize = True).sort_index() * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It turns out that only 31.7% of the participants have a clear idea about what programming niche they'd like to work in, while the vast majority of students have mixed interests. But given that we offer courses on various subjects, the fact that new coders have mixed interest might be actually good for us.\n",
    "\n",
    "The focus of our courses is on web and mobile development, so let's find out how many respondents chose at least one of these two options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True     86.241419\n",
      "False    13.758581\n",
      "Name: JobRoleInterest, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Frequency table\n",
    "web_or_mobile = interests_no_nulls.str.contains(\n",
    "    'Web Developer|Mobile Developer') # returns an array of booleans\n",
    "freq_table = web_or_mobile.value_counts(normalize = True) * 100\n",
    "print(freq_table)\n",
    "\n",
    "# Graph for the frequency table above\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('fivethirtyeight')\n",
    "\n",
    "freq_table.plot.bar()\n",
    "plt.title('Most Participants are Interested in \\nWeb or Mobile Development',\n",
    "          y = 1.08) # y pads the title upward\n",
    "plt.ylabel('Percentage', fontsize = 12)\n",
    "plt.xticks([0,1],['Web or mobile\\ndevelopment', 'Other subject'],\n",
    "           rotation = 0) # the initial xtick labels were True and False\n",
    "plt.ylim([0,100])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "It turns out that most people in this survey (roughly 86%) are interested in either web or mobile development. These figures offer us a strong reason to consider this sample representative for our population of interest. We want to advertise our courses to people interested in all sorts of programming niches but mostly web and mobile development.\n",
    "\n",
    "Now we need to figure out what are the best markets to invest money in for advertising our courses. We'd like to know:\n",
    "\n",
    "* Where are these new coders located.\n",
    "* What are the locations with the greatest number of new coders.\n",
    "* How much money new coders are willing to spend on learning."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# New Coders - Locations and Densities\n",
    "\n",
    "Let's begin with finding out where these new coders are located, and what are the densities (how many new coders there are) for each location. This should be a good start for finding out the best two markets to run our ads campaign in.\n",
    "\n",
    "The data set provides information about the location of each participant at a country level. We can think of each country as an individual market, so we can frame our goal as finding the two best countries to advertise in.\n",
    "\n",
    "We can start by examining the frequency distribution table of the CountryLive variable, which describes what country each participant lives in (not their origin country). We'll only consider those participants who answered what role(s) they're interested in, to make sure we work with a representative sample."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Absolute frequency</th>\n",
       "      <th>Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>United States of America</th>\n",
       "      <td>3125</td>\n",
       "      <td>45.700497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>528</td>\n",
       "      <td>7.721556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Kingdom</th>\n",
       "      <td>315</td>\n",
       "      <td>4.606610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>260</td>\n",
       "      <td>3.802281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Poland</th>\n",
       "      <td>131</td>\n",
       "      <td>1.915765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Guatemala</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Papua New Guinea</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Channel Islands</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jordan</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kyrgyzstan</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>137 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Absolute frequency  Percentage\n",
       "United States of America                3125   45.700497\n",
       "India                                    528    7.721556\n",
       "United Kingdom                           315    4.606610\n",
       "Canada                                   260    3.802281\n",
       "Poland                                   131    1.915765\n",
       "...                                      ...         ...\n",
       "Guatemala                                  1    0.014624\n",
       "Papua New Guinea                           1    0.014624\n",
       "Channel Islands                            1    0.014624\n",
       "Jordan                                     1    0.014624\n",
       "Kyrgyzstan                                 1    0.014624\n",
       "\n",
       "[137 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Isolate the participants that answered what role they'd be interested in\n",
    "fcc_good = fcc[fcc['JobRoleInterest'].notnull()].copy()\n",
    "\n",
    "# Frequency tables with absolute and relative frequencies\n",
    "absolute_frequencies = fcc_good['CountryLive'].value_counts()\n",
    "relative_frequencies = fcc_good['CountryLive'].value_counts(normalize = True) * 100\n",
    "\n",
    "# Display the frequency tables in a more readable format\n",
    "pd.DataFrame(data = {'Absolute frequency': absolute_frequencies, \n",
    "                     'Percentage': relative_frequencies}\n",
    "            )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "45.7% of our potential customers are located in the US, and this definitely seems like the most interesting market. India has the second customer density, but it's just 7.7%, which is not too far from the United Kingdom (4.6%) or Canada (3.8%).\n",
    "\n",
    "This is useful information, but we need to go more in depth than this and figure out how much money people are actually willing to spend on learning. Advertising in high-density markets where most people are only willing to learn for free is extremely unlikely to be profitable for us.\n",
    "\n",
    "# Spending Money for Learning\n",
    "\n",
    "The MoneyForLearning column describes in American dollars the amount of money spent by participants from the moment they started coding until the moment they completed the survey. Our company sells subscriptions at a price of \\$59 per month, and for this reason we're interested in finding out how much money each student spends per month.\n",
    "\n",
    "We'll narrow down our analysis to only four countries: the US, India, the United Kingdom, and Canada. We do this for two reasons:\n",
    "\n",
    "These are the countries having the highest frequency in the frequency table above, which means we have a decent amount of data for each.\n",
    "Our courses are written in English, and English is an official language in all these four countries. The more people know English, the better our chances to target the right people with our ads.\n",
    "Let's start with creating a new column that describes the amount of money a student has spent per month so far. To do that, we'll need to divide the MoneyForLearning column to the MonthsProgramming column. The problem is that some students answered that they have been learning to code for 0 months (it might be that they have just started). To avoid dividing by 0, we'll replace 0 with 1 in the MonthsProgramming column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "675"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Replace 0s with 1s to avoid division by 0\n",
    "fcc_good['MonthsProgramming'].replace(0,1, inplace = True)\n",
    "\n",
    "# New column for the amount of money each student spends each month\n",
    "fcc_good['money_per_month'] = fcc_good['MoneyForLearning'] / fcc_good['MonthsProgramming']\n",
    "fcc_good['money_per_month'].isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's keep only the rows that don't have null values for the money_per_month column.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Keep only the rows with non-nulls in the `money_per_month` column \n",
    "fcc_good = fcc_good[fcc_good['money_per_month'].notnull()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to group the data by country, and then measure the average amount of money that students spend per month in each country. First, let's remove the rows having null values for the CountryLive column, and check out if we still have enough data for the four countries that interest us.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "United States of America    2933\n",
       "India                        463\n",
       "United Kingdom               279\n",
       "Canada                       240\n",
       "Poland                       122\n",
       "Name: CountryLive, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove the rows with null values in 'CountryLive'\n",
    "fcc_good = fcc_good[fcc_good['CountryLive'].notnull()]\n",
    "\n",
    "# Frequency table to check if we still have enough data\n",
    "fcc_good['CountryLive'].value_counts().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This should be enough, so let's compute the average value spent per month in each country by a student. We'll compute the average using the mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CountryLive\n",
       "United States of America    227.997996\n",
       "India                       135.100982\n",
       "United Kingdom               45.534443\n",
       "Canada                      113.510961\n",
       "Name: money_per_month, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Mean sum of money spent by students each month\n",
    "countries_mean = fcc_good.groupby('CountryLive').mean()\n",
    "countries_mean['money_per_month'][['United States of America',\n",
    "                            'India', 'United Kingdom',\n",
    "                            'Canada']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results for the United Kingdom and Canada are a bit surprising relative to the values we see for India. If we considered a few socio-economical metrics (like GDP per capita), we'd intuitively expect people in the UK and Canada to spend more on learning than people in India.\n",
    "\n",
    "It might be that we don't have have enough representative data for the United Kingdom and Canada, or we have some outliers (maybe coming from wrong survey answers) making the mean too large for India, or too low for the UK and Canada. Or it might be that the results are correct."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dealing with Extreme Outliers\n",
    "\n",
    "Let's use box plots to visualize the distribution of the money_per_month variable for each country."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Isolate only the countries of interest\n",
    "only_4 = fcc_good[fcc_good['CountryLive'].str.contains(\n",
    "    'United States of America|India|United Kingdom|Canada')]\n",
    "\n",
    "# Box plots to visualize distributions\n",
    "import seaborn as sns\n",
    "sns.boxplot(y = 'money_per_month', x = 'CountryLive',\n",
    "            data = only_4)\n",
    "plt.title('Money Spent Per Month Per Country\\n(Distributions)',\n",
    "         fontsize = 16)\n",
    "plt.ylabel('Money per month (US dollars)')\n",
    "plt.xlabel('Country')\n",
    "plt.xticks(range(4), ['US', 'UK', 'India', 'Canada']) # avoids tick labels overlap\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's hard to see on the plot above if there's anything wrong with the data for the United Kingdom, India, or Canada, but we can see immediately that there's something really off for the US: two persons spend each month $ $50000$ or more for learning.\n",
    "\n",
    "\n",
    "This is not impossible, but it seems extremely unlikely, so we'll remove every value that goes over $20,000 per month."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Isolate only those participants who spend less than 10000 per month\n",
    "fcc_good = fcc_good[fcc_good['money_per_month'] < 20000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's recompute the mean values and plot the box plots again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CountryLive\n",
       "United States of America    183.800110\n",
       "India                       135.100982\n",
       "United Kingdom               45.534443\n",
       "Canada                      113.510961\n",
       "Name: money_per_month, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Recompute mean sum of money spent by students each month\n",
    "countries_mean = fcc_good.groupby('CountryLive').mean()\n",
    "countries_mean['money_per_month'][['United States of America',\n",
    "                            'India', 'United Kingdom',\n",
    "                            'Canada']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Isolate again the countries of interest\n",
    "only_4 = fcc_good[fcc_good['CountryLive'].str.contains(\n",
    "    'United States of America|India|United Kingdom|Canada')]\n",
    "\n",
    "# Box plots to visualize distributions\n",
    "sns.boxplot(y = 'money_per_month', x = 'CountryLive',\n",
    "            data = only_4)\n",
    "plt.title('Money Spent Per Month Per Country\\n(Distributions)',\n",
    "         fontsize = 16)\n",
    "plt.ylabel('Money per month (US dollars)')\n",
    "plt.xlabel('Country')\n",
    "plt.xticks(range(4), ['US', 'UK', 'India', 'Canada']) # avoids tick labels overlap\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see a few extreme outliers for India (values over \\$2500 per month), but it's unclear whether this is good data or not. Maybe these persons attended several bootcamps, which tend to be very expensive. Let's examine these two data points to see if we can find anything relevant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Age</th>\n",
       "      <th>AttendedBootcamp</th>\n",
       "      <th>BootcampFinish</th>\n",
       "      <th>BootcampLoanYesNo</th>\n",
       "      <th>BootcampName</th>\n",
       "      <th>BootcampRecommend</th>\n",
       "      <th>ChildrenNumber</th>\n",
       "      <th>CityPopulation</th>\n",
       "      <th>CodeEventConferences</th>\n",
       "      <th>CodeEventDjangoGirls</th>\n",
       "      <th>CodeEventFCC</th>\n",
       "      <th>CodeEventGameJam</th>\n",
       "      <th>CodeEventGirlDev</th>\n",
       "      <th>CodeEventHackathons</th>\n",
       "      <th>CodeEventMeetup</th>\n",
       "      <th>CodeEventNodeSchool</th>\n",
       "      <th>CodeEventNone</th>\n",
       "      <th>CodeEventOther</th>\n",
       "      <th>CodeEventRailsBridge</th>\n",
       "      <th>CodeEventRailsGirls</th>\n",
       "      <th>CodeEventStartUpWknd</th>\n",
       "      <th>CodeEventWkdBootcamps</th>\n",
       "      <th>CodeEventWomenCode</th>\n",
       "      <th>CodeEventWorkshops</th>\n",
       "      <th>CommuteTime</th>\n",
       "      <th>CountryCitizen</th>\n",
       "      <th>CountryLive</th>\n",
       "      <th>EmploymentField</th>\n",
       "      <th>EmploymentFieldOther</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>EmploymentStatusOther</th>\n",
       "      <th>ExpectedEarning</th>\n",
       "      <th>FinanciallySupporting</th>\n",
       "      <th>FirstDevJob</th>\n",
       "      <th>Gender</th>\n",
       "      <th>GenderOther</th>\n",
       "      <th>HasChildren</th>\n",
       "      <th>HasDebt</th>\n",
       "      <th>HasFinancialDependents</th>\n",
       "      <th>HasHighSpdInternet</th>\n",
       "      <th>HasHomeMortgage</th>\n",
       "      <th>HasServedInMilitary</th>\n",
       "      <th>HasStudentDebt</th>\n",
       "      <th>HomeMortgageOwe</th>\n",
       "      <th>HoursLearning</th>\n",
       "      <th>ID.x</th>\n",
       "      <th>ID.y</th>\n",
       "      <th>Income</th>\n",
       "      <th>IsEthnicMinority</th>\n",
       "      <th>IsReceiveDisabilitiesBenefits</th>\n",
       "      <th>IsSoftwareDev</th>\n",
       "      <th>IsUnderEmployed</th>\n",
       "      <th>JobApplyWhen</th>\n",
       "      <th>JobInterestBackEnd</th>\n",
       "      <th>JobInterestDataEngr</th>\n",
       "      <th>JobInterestDataSci</th>\n",
       "      <th>JobInterestDevOps</th>\n",
       "      <th>JobInterestFrontEnd</th>\n",
       "      <th>JobInterestFullStack</th>\n",
       "      <th>JobInterestGameDev</th>\n",
       "      <th>JobInterestInfoSec</th>\n",
       "      <th>JobInterestMobile</th>\n",
       "      <th>JobInterestOther</th>\n",
       "      <th>JobInterestProjMngr</th>\n",
       "      <th>JobInterestQAEngr</th>\n",
       "      <th>JobInterestUX</th>\n",
       "      <th>JobPref</th>\n",
       "      <th>JobRelocateYesNo</th>\n",
       "      <th>JobRoleInterest</th>\n",
       "      <th>JobWherePref</th>\n",
       "      <th>LanguageAtHome</th>\n",
       "      <th>MaritalStatus</th>\n",
       "      <th>MoneyForLearning</th>\n",
       "      <th>MonthsProgramming</th>\n",
       "      <th>NetworkID</th>\n",
       "      <th>Part1EndTime</th>\n",
       "      <th>Part1StartTime</th>\n",
       "      <th>Part2EndTime</th>\n",
       "      <th>Part2StartTime</th>\n",
       "      <th>PodcastChangeLog</th>\n",
       "      <th>PodcastCodeNewbie</th>\n",
       "      <th>PodcastCodePen</th>\n",
       "      <th>PodcastDevTea</th>\n",
       "      <th>PodcastDotNET</th>\n",
       "      <th>PodcastGiantRobots</th>\n",
       "      <th>PodcastJSAir</th>\n",
       "      <th>PodcastJSJabber</th>\n",
       "      <th>PodcastNone</th>\n",
       "      <th>PodcastOther</th>\n",
       "      <th>PodcastProgThrowdown</th>\n",
       "      <th>PodcastRubyRogues</th>\n",
       "      <th>PodcastSEDaily</th>\n",
       "      <th>PodcastSERadio</th>\n",
       "      <th>PodcastShopTalk</th>\n",
       "      <th>PodcastTalkPython</th>\n",
       "      <th>PodcastTheWebAhead</th>\n",
       "      <th>ResourceCodecademy</th>\n",
       "      <th>ResourceCodeWars</th>\n",
       "      <th>ResourceCoursera</th>\n",
       "      <th>ResourceCSS</th>\n",
       "      <th>ResourceEdX</th>\n",
       "      <th>ResourceEgghead</th>\n",
       "      <th>ResourceFCC</th>\n",
       "      <th>ResourceHackerRank</th>\n",
       "      <th>ResourceKA</th>\n",
       "      <th>ResourceLynda</th>\n",
       "      <th>ResourceMDN</th>\n",
       "      <th>ResourceOdinProj</th>\n",
       "      <th>ResourceOther</th>\n",
       "      <th>ResourcePluralSight</th>\n",
       "      <th>ResourceSkillcrush</th>\n",
       "      <th>ResourceSO</th>\n",
       "      <th>ResourceTreehouse</th>\n",
       "      <th>ResourceUdacity</th>\n",
       "      <th>ResourceUdemy</th>\n",
       "      <th>ResourceW3S</th>\n",
       "      <th>SchoolDegree</th>\n",
       "      <th>SchoolMajor</th>\n",
       "      <th>StudentDebtOwe</th>\n",
       "      <th>YouTubeCodeCourse</th>\n",
       "      <th>YouTubeCodingTrain</th>\n",
       "      <th>YouTubeCodingTut360</th>\n",
       "      <th>YouTubeComputerphile</th>\n",
       "      <th>YouTubeDerekBanas</th>\n",
       "      <th>YouTubeDevTips</th>\n",
       "      <th>YouTubeEngineeredTruth</th>\n",
       "      <th>YouTubeFCC</th>\n",
       "      <th>YouTubeFunFunFunction</th>\n",
       "      <th>YouTubeGoogleDev</th>\n",
       "      <th>YouTubeLearnCode</th>\n",
       "      <th>YouTubeLevelUpTuts</th>\n",
       "      <th>YouTubeMIT</th>\n",
       "      <th>YouTubeMozillaHacks</th>\n",
       "      <th>YouTubeOther</th>\n",
       "      <th>YouTubeSimplilearn</th>\n",
       "      <th>YouTubeTheNewBoston</th>\n",
       "      <th>money_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1728</th>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>between 100,000 and 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>India</td>\n",
       "      <td>India</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A stay-at-home parent or homemaker</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.0</td>\n",
       "      <td>d964ec629fd6d85a5bf27f7339f4fa6d</td>\n",
       "      <td>950a8cf9cef1ae6a15da470e572b1b7a</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Within the next 6 months</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>work for a startup</td>\n",
       "      <td>1.0</td>\n",
       "      <td>User Experience Designer,   Mobile Developer...</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>Bengali</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>38d312a990</td>\n",
       "      <td>2017-03-10 10:22:34</td>\n",
       "      <td>2017-03-10 10:17:42</td>\n",
       "      <td>2017-03-10 10:24:38</td>\n",
       "      <td>2017-03-10 10:22:40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Computer Programming</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1755</th>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>India</td>\n",
       "      <td>India</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not working and not looking for work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>811bf953ef546460f5436fcf2baa532d</td>\n",
       "      <td>81e2a4cab0543e14746c4a20ffdae17c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>I haven't decided</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a multinational corporation</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Information Security, Full-Stack Web Developer...</td>\n",
       "      <td>no preference</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>4611a76b60</td>\n",
       "      <td>2017-03-10 10:48:31</td>\n",
       "      <td>2017-03-10 10:42:29</td>\n",
       "      <td>2017-03-10 10:51:37</td>\n",
       "      <td>2017-03-10 10:48:38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Computer Science</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3333.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7989</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>between 100,000 and 1 million</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15 to 29 minutes</td>\n",
       "      <td>India</td>\n",
       "      <td>India</td>\n",
       "      <td>software development and IT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>a6a5597bbbc2c282386d6675641b744a</td>\n",
       "      <td>da7bbb54a8b26a379707be56b6c51e65</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>more than 12 months from now</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>work for a multinational corporation</td>\n",
       "      <td>1.0</td>\n",
       "      <td>User Experience Designer, Back-End Web Devel...</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>Marathi</td>\n",
       "      <td>married or domestic partnership</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>c47a447b5d</td>\n",
       "      <td>2017-03-26 14:06:48</td>\n",
       "      <td>2017-03-26 14:02:41</td>\n",
       "      <td>2017-03-26 14:13:13</td>\n",
       "      <td>2017-03-26 14:07:17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not listened to anything yet.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Aerospace and Aeronautical Engineering</td>\n",
       "      <td>2500.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8126</th>\n",
       "      <td>22.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>India</td>\n",
       "      <td>India</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not working but looking for work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.0</td>\n",
       "      <td>69e8ab9126baee49f66e3577aea7fd3c</td>\n",
       "      <td>9f08092e82f709e63847ba88841247c0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>I'm already applying</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a startup</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Back-End Web Developer, Full-Stack Web Develop...</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>Malayalam</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0d3d1762a4</td>\n",
       "      <td>2017-03-27 07:10:17</td>\n",
       "      <td>2017-03-27 07:05:23</td>\n",
       "      <td>2017-03-27 07:12:21</td>\n",
       "      <td>2017-03-27 07:10:22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Electrical and Electronics Engineering</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13398</th>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>India</td>\n",
       "      <td>India</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unable to work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.0</td>\n",
       "      <td>b7fe7bc4edefc3a60eb48f977e4426e3</td>\n",
       "      <td>80ff09859ac475b70ac19b7b7369e953</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>I haven't decided</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a multinational corporation</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Mobile Developer</td>\n",
       "      <td>no preference</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>51a6f9a1a7</td>\n",
       "      <td>2017-04-01 00:31:25</td>\n",
       "      <td>2017-04-01 00:28:17</td>\n",
       "      <td>2017-04-01 00:33:44</td>\n",
       "      <td>2017-04-01 00:31:32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Computer Science</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15587</th>\n",
       "      <td>27.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15 to 29 minutes</td>\n",
       "      <td>India</td>\n",
       "      <td>India</td>\n",
       "      <td>software development and IT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.0</td>\n",
       "      <td>5a7394f24292cb82b72adb702886543a</td>\n",
       "      <td>8bc7997217d4a57b22242471cc8d89ef</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>I haven't decided</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a startup</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Full-Stack Web Developer,   Data Scientist</td>\n",
       "      <td>from home</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>8af0c2b6da</td>\n",
       "      <td>2017-04-03 09:43:53</td>\n",
       "      <td>2017-04-03 09:39:38</td>\n",
       "      <td>2017-04-03 09:54:39</td>\n",
       "      <td>2017-04-03 09:43:57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Communications</td>\n",
       "      <td>25000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4166.666667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Age  AttendedBootcamp  BootcampFinish  BootcampLoanYesNo BootcampName  \\\n",
       "1728   24.0               0.0             NaN                NaN          NaN   \n",
       "1755   20.0               0.0             NaN                NaN          NaN   \n",
       "7989   28.0               0.0             NaN                NaN          NaN   \n",
       "8126   22.0               0.0             NaN                NaN          NaN   \n",
       "13398  19.0               0.0             NaN                NaN          NaN   \n",
       "15587  27.0               0.0             NaN                NaN          NaN   \n",
       "\n",
       "       BootcampRecommend  ChildrenNumber                 CityPopulation  \\\n",
       "1728                 NaN             NaN  between 100,000 and 1 million   \n",
       "1755                 NaN             NaN            more than 1 million   \n",
       "7989                 NaN             NaN  between 100,000 and 1 million   \n",
       "8126                 NaN             NaN            more than 1 million   \n",
       "13398                NaN             NaN            more than 1 million   \n",
       "15587                NaN             NaN            more than 1 million   \n",
       "\n",
       "       CodeEventConferences  CodeEventDjangoGirls  CodeEventFCC  \\\n",
       "1728                    NaN                   NaN           NaN   \n",
       "1755                    NaN                   NaN           1.0   \n",
       "7989                    1.0                   NaN           NaN   \n",
       "8126                    NaN                   NaN           NaN   \n",
       "13398                   NaN                   NaN           NaN   \n",
       "15587                   NaN                   NaN           NaN   \n",
       "\n",
       "       CodeEventGameJam  CodeEventGirlDev  CodeEventHackathons  \\\n",
       "1728                1.0               NaN                  NaN   \n",
       "1755                NaN               NaN                  1.0   \n",
       "7989                NaN               NaN                  NaN   \n",
       "8126                1.0               NaN                  1.0   \n",
       "13398               NaN               NaN                  NaN   \n",
       "15587               NaN               NaN                  1.0   \n",
       "\n",
       "       CodeEventMeetup  CodeEventNodeSchool  CodeEventNone CodeEventOther  \\\n",
       "1728               NaN                  NaN            NaN            NaN   \n",
       "1755               1.0                  NaN            NaN            NaN   \n",
       "7989               NaN                  NaN            NaN            NaN   \n",
       "8126               NaN                  NaN            NaN            NaN   \n",
       "13398              NaN                  NaN            1.0            NaN   \n",
       "15587              NaN                  NaN            NaN            NaN   \n",
       "\n",
       "       CodeEventRailsBridge  CodeEventRailsGirls  CodeEventStartUpWknd  \\\n",
       "1728                    NaN                  NaN                   NaN   \n",
       "1755                    NaN                  NaN                   NaN   \n",
       "7989                    NaN                  NaN                   NaN   \n",
       "8126                    NaN                  NaN                   NaN   \n",
       "13398                   NaN                  NaN                   NaN   \n",
       "15587                   NaN                  NaN                   NaN   \n",
       "\n",
       "       CodeEventWkdBootcamps  CodeEventWomenCode  CodeEventWorkshops  \\\n",
       "1728                     NaN                 NaN                 NaN   \n",
       "1755                     NaN                 NaN                 NaN   \n",
       "7989                     NaN                 NaN                 1.0   \n",
       "8126                     NaN                 NaN                 NaN   \n",
       "13398                    NaN                 NaN                 NaN   \n",
       "15587                    NaN                 NaN                 NaN   \n",
       "\n",
       "            CommuteTime CountryCitizen CountryLive  \\\n",
       "1728                NaN          India       India   \n",
       "1755                NaN          India       India   \n",
       "7989   15 to 29 minutes          India       India   \n",
       "8126                NaN          India       India   \n",
       "13398               NaN          India       India   \n",
       "15587  15 to 29 minutes          India       India   \n",
       "\n",
       "                   EmploymentField EmploymentFieldOther  \\\n",
       "1728                           NaN                  NaN   \n",
       "1755                           NaN                  NaN   \n",
       "7989   software development and IT                  NaN   \n",
       "8126                           NaN                  NaN   \n",
       "13398                          NaN                  NaN   \n",
       "15587  software development and IT                  NaN   \n",
       "\n",
       "                           EmploymentStatus EmploymentStatusOther  \\\n",
       "1728     A stay-at-home parent or homemaker                   NaN   \n",
       "1755   Not working and not looking for work                   NaN   \n",
       "7989                     Employed for wages                   NaN   \n",
       "8126       Not working but looking for work                   NaN   \n",
       "13398                        Unable to work                   NaN   \n",
       "15587                    Employed for wages                   NaN   \n",
       "\n",
       "       ExpectedEarning  FinanciallySupporting  FirstDevJob Gender GenderOther  \\\n",
       "1728           70000.0                    NaN          NaN   male         NaN   \n",
       "1755          100000.0                    NaN          NaN   male         NaN   \n",
       "7989          500000.0                    1.0          NaN   male         NaN   \n",
       "8126           80000.0                    NaN          NaN   male         NaN   \n",
       "13398         100000.0                    NaN          NaN   male         NaN   \n",
       "15587          65000.0                    0.0          NaN   male         NaN   \n",
       "\n",
       "       HasChildren  HasDebt  HasFinancialDependents  HasHighSpdInternet  \\\n",
       "1728           NaN      0.0                     0.0                 1.0   \n",
       "1755           NaN      0.0                     0.0                 1.0   \n",
       "7989           0.0      1.0                     1.0                 1.0   \n",
       "8126           NaN      1.0                     0.0                 1.0   \n",
       "13398          NaN      0.0                     0.0                 0.0   \n",
       "15587          0.0      1.0                     1.0                 1.0   \n",
       "\n",
       "       HasHomeMortgage  HasServedInMilitary  HasStudentDebt  HomeMortgageOwe  \\\n",
       "1728               NaN                  0.0             NaN              NaN   \n",
       "1755               NaN                  0.0             NaN              NaN   \n",
       "7989               0.0                  0.0             1.0              NaN   \n",
       "8126               0.0                  0.0             1.0              NaN   \n",
       "13398              NaN                  0.0             NaN              NaN   \n",
       "15587              0.0                  0.0             1.0              NaN   \n",
       "\n",
       "       HoursLearning                              ID.x  \\\n",
       "1728            30.0  d964ec629fd6d85a5bf27f7339f4fa6d   \n",
       "1755            10.0  811bf953ef546460f5436fcf2baa532d   \n",
       "7989            20.0  a6a5597bbbc2c282386d6675641b744a   \n",
       "8126            80.0  69e8ab9126baee49f66e3577aea7fd3c   \n",
       "13398           30.0  b7fe7bc4edefc3a60eb48f977e4426e3   \n",
       "15587           36.0  5a7394f24292cb82b72adb702886543a   \n",
       "\n",
       "                                   ID.y    Income  IsEthnicMinority  \\\n",
       "1728   950a8cf9cef1ae6a15da470e572b1b7a       NaN               0.0   \n",
       "1755   81e2a4cab0543e14746c4a20ffdae17c       NaN               0.0   \n",
       "7989   da7bbb54a8b26a379707be56b6c51e65  300000.0               0.0   \n",
       "8126   9f08092e82f709e63847ba88841247c0       NaN               0.0   \n",
       "13398  80ff09859ac475b70ac19b7b7369e953       NaN               0.0   \n",
       "15587  8bc7997217d4a57b22242471cc8d89ef   60000.0               0.0   \n",
       "\n",
       "       IsReceiveDisabilitiesBenefits  IsSoftwareDev  IsUnderEmployed  \\\n",
       "1728                             0.0            0.0              NaN   \n",
       "1755                             0.0            0.0              NaN   \n",
       "7989                             0.0            0.0              0.0   \n",
       "8126                             0.0            0.0              NaN   \n",
       "13398                            0.0            0.0              NaN   \n",
       "15587                            0.0            0.0              1.0   \n",
       "\n",
       "                       JobApplyWhen  JobInterestBackEnd  JobInterestDataEngr  \\\n",
       "1728       Within the next 6 months                 1.0                  NaN   \n",
       "1755              I haven't decided                 NaN                  1.0   \n",
       "7989   more than 12 months from now                 1.0                  NaN   \n",
       "8126           I'm already applying                 1.0                  NaN   \n",
       "13398             I haven't decided                 NaN                  NaN   \n",
       "15587             I haven't decided                 NaN                  NaN   \n",
       "\n",
       "       JobInterestDataSci  JobInterestDevOps  JobInterestFrontEnd  \\\n",
       "1728                  NaN                NaN                  1.0   \n",
       "1755                  NaN                1.0                  1.0   \n",
       "7989                  NaN                NaN                  1.0   \n",
       "8126                  NaN                NaN                  1.0   \n",
       "13398                 NaN                NaN                  NaN   \n",
       "15587                 1.0                NaN                  NaN   \n",
       "\n",
       "       JobInterestFullStack  JobInterestGameDev  JobInterestInfoSec  \\\n",
       "1728                    NaN                 NaN                 NaN   \n",
       "1755                    1.0                 NaN                 1.0   \n",
       "7989                    1.0                 1.0                 NaN   \n",
       "8126                    1.0                 NaN                 NaN   \n",
       "13398                   NaN                 NaN                 NaN   \n",
       "15587                   1.0                 NaN                 NaN   \n",
       "\n",
       "       JobInterestMobile JobInterestOther  JobInterestProjMngr  \\\n",
       "1728                 1.0              NaN                  1.0   \n",
       "1755                 NaN              NaN                  NaN   \n",
       "7989                 NaN              NaN                  NaN   \n",
       "8126                 NaN              NaN                  NaN   \n",
       "13398                1.0              NaN                  NaN   \n",
       "15587                NaN              NaN                  NaN   \n",
       "\n",
       "       JobInterestQAEngr  JobInterestUX                               JobPref  \\\n",
       "1728                 NaN            1.0                    work for a startup   \n",
       "1755                 NaN            NaN  work for a multinational corporation   \n",
       "7989                 NaN            1.0  work for a multinational corporation   \n",
       "8126                 NaN            NaN                    work for a startup   \n",
       "13398                NaN            NaN  work for a multinational corporation   \n",
       "15587                NaN            NaN                    work for a startup   \n",
       "\n",
       "       JobRelocateYesNo                                    JobRoleInterest  \\\n",
       "1728                1.0    User Experience Designer,   Mobile Developer...   \n",
       "1755                1.0  Information Security, Full-Stack Web Developer...   \n",
       "7989                1.0    User Experience Designer, Back-End Web Devel...   \n",
       "8126                1.0  Back-End Web Developer, Full-Stack Web Develop...   \n",
       "13398               1.0                                   Mobile Developer   \n",
       "15587               NaN         Full-Stack Web Developer,   Data Scientist   \n",
       "\n",
       "                             JobWherePref LanguageAtHome  \\\n",
       "1728   in an office with other developers        Bengali   \n",
       "1755                        no preference          Hindi   \n",
       "7989   in an office with other developers        Marathi   \n",
       "8126   in an office with other developers      Malayalam   \n",
       "13398                       no preference          Hindi   \n",
       "15587                           from home          Hindi   \n",
       "\n",
       "                         MaritalStatus  MoneyForLearning  MonthsProgramming  \\\n",
       "1728             single, never married           20000.0                4.0   \n",
       "1755             single, never married           50000.0               15.0   \n",
       "7989   married or domestic partnership            5000.0                1.0   \n",
       "8126             single, never married            5000.0                1.0   \n",
       "13398            single, never married           20000.0                2.0   \n",
       "15587            single, never married          100000.0               24.0   \n",
       "\n",
       "        NetworkID         Part1EndTime       Part1StartTime  \\\n",
       "1728   38d312a990  2017-03-10 10:22:34  2017-03-10 10:17:42   \n",
       "1755   4611a76b60  2017-03-10 10:48:31  2017-03-10 10:42:29   \n",
       "7989   c47a447b5d  2017-03-26 14:06:48  2017-03-26 14:02:41   \n",
       "8126   0d3d1762a4  2017-03-27 07:10:17  2017-03-27 07:05:23   \n",
       "13398  51a6f9a1a7  2017-04-01 00:31:25  2017-04-01 00:28:17   \n",
       "15587  8af0c2b6da  2017-04-03 09:43:53  2017-04-03 09:39:38   \n",
       "\n",
       "              Part2EndTime       Part2StartTime  PodcastChangeLog  \\\n",
       "1728   2017-03-10 10:24:38  2017-03-10 10:22:40               NaN   \n",
       "1755   2017-03-10 10:51:37  2017-03-10 10:48:38               NaN   \n",
       "7989   2017-03-26 14:13:13  2017-03-26 14:07:17               NaN   \n",
       "8126   2017-03-27 07:12:21  2017-03-27 07:10:22               NaN   \n",
       "13398  2017-04-01 00:33:44  2017-04-01 00:31:32               NaN   \n",
       "15587  2017-04-03 09:54:39  2017-04-03 09:43:57               NaN   \n",
       "\n",
       "       PodcastCodeNewbie  PodcastCodePen  PodcastDevTea  PodcastDotNET  \\\n",
       "1728                 NaN             NaN            NaN            NaN   \n",
       "1755                 NaN             NaN            NaN            NaN   \n",
       "7989                 NaN             NaN            NaN            NaN   \n",
       "8126                 NaN             NaN            NaN            NaN   \n",
       "13398                NaN             NaN            NaN            NaN   \n",
       "15587                NaN             NaN            NaN            NaN   \n",
       "\n",
       "       PodcastGiantRobots  PodcastJSAir  PodcastJSJabber  PodcastNone  \\\n",
       "1728                  NaN           1.0              NaN          NaN   \n",
       "1755                  NaN           NaN              NaN          NaN   \n",
       "7989                  NaN           NaN              NaN          NaN   \n",
       "8126                  NaN           NaN              NaN          NaN   \n",
       "13398                 NaN           NaN              NaN          NaN   \n",
       "15587                 NaN           NaN              NaN          NaN   \n",
       "\n",
       "                        PodcastOther  PodcastProgThrowdown  PodcastRubyRogues  \\\n",
       "1728                             NaN                   NaN                NaN   \n",
       "1755                             NaN                   NaN                NaN   \n",
       "7989   Not listened to anything yet.                   NaN                NaN   \n",
       "8126                             NaN                   NaN                NaN   \n",
       "13398                            NaN                   NaN                NaN   \n",
       "15587                            NaN                   1.0                NaN   \n",
       "\n",
       "       PodcastSEDaily  PodcastSERadio  PodcastShopTalk  PodcastTalkPython  \\\n",
       "1728              NaN             NaN              NaN                NaN   \n",
       "1755              1.0             NaN              NaN                NaN   \n",
       "7989              NaN             NaN              NaN                NaN   \n",
       "8126              NaN             NaN              NaN                NaN   \n",
       "13398             NaN             NaN              NaN                NaN   \n",
       "15587             NaN             NaN              NaN                NaN   \n",
       "\n",
       "       PodcastTheWebAhead  ResourceCodecademy  ResourceCodeWars  \\\n",
       "1728                  NaN                 1.0               NaN   \n",
       "1755                  NaN                 1.0               1.0   \n",
       "7989                  NaN                 NaN               NaN   \n",
       "8126                  NaN                 NaN               NaN   \n",
       "13398                 NaN                 NaN               NaN   \n",
       "15587                 NaN                 NaN               NaN   \n",
       "\n",
       "       ResourceCoursera  ResourceCSS  ResourceEdX  ResourceEgghead  \\\n",
       "1728                NaN          NaN          NaN              NaN   \n",
       "1755                1.0          NaN          1.0              NaN   \n",
       "7989                NaN          NaN          NaN              NaN   \n",
       "8126                NaN          1.0          NaN              1.0   \n",
       "13398               NaN          NaN          NaN              NaN   \n",
       "15587               NaN          NaN          1.0              NaN   \n",
       "\n",
       "       ResourceFCC  ResourceHackerRank  ResourceKA  ResourceLynda  \\\n",
       "1728           NaN                 NaN         NaN            NaN   \n",
       "1755           1.0                 NaN         1.0            1.0   \n",
       "7989           1.0                 NaN         NaN            1.0   \n",
       "8126           NaN                 NaN         NaN            NaN   \n",
       "13398          NaN                 NaN         NaN            NaN   \n",
       "15587          1.0                 NaN         NaN            1.0   \n",
       "\n",
       "       ResourceMDN  ResourceOdinProj ResourceOther  ResourcePluralSight  \\\n",
       "1728           NaN               NaN           NaN                  NaN   \n",
       "1755           NaN               NaN           NaN                  1.0   \n",
       "7989           NaN               NaN           NaN                  NaN   \n",
       "8126           NaN               NaN           NaN                  NaN   \n",
       "13398          NaN               NaN           NaN                  NaN   \n",
       "15587          NaN               NaN           NaN                  NaN   \n",
       "\n",
       "       ResourceSkillcrush  ResourceSO  ResourceTreehouse  ResourceUdacity  \\\n",
       "1728                  NaN         NaN                NaN              NaN   \n",
       "1755                  NaN         NaN                NaN              1.0   \n",
       "7989                  NaN         NaN                NaN              NaN   \n",
       "8126                  NaN         1.0                NaN              NaN   \n",
       "13398                 NaN         1.0                NaN              NaN   \n",
       "15587                 NaN         1.0                NaN              NaN   \n",
       "\n",
       "       ResourceUdemy  ResourceW3S       SchoolDegree  \\\n",
       "1728             1.0          1.0  bachelor's degree   \n",
       "1755             1.0          1.0  bachelor's degree   \n",
       "7989             NaN          NaN  bachelor's degree   \n",
       "8126             NaN          NaN  bachelor's degree   \n",
       "13398            NaN          1.0  bachelor's degree   \n",
       "15587            NaN          1.0  bachelor's degree   \n",
       "\n",
       "                                  SchoolMajor  StudentDebtOwe  \\\n",
       "1728                     Computer Programming             NaN   \n",
       "1755                         Computer Science             NaN   \n",
       "7989   Aerospace and Aeronautical Engineering          2500.0   \n",
       "8126   Electrical and Electronics Engineering         10000.0   \n",
       "13398                        Computer Science             NaN   \n",
       "15587                          Communications         25000.0   \n",
       "\n",
       "       YouTubeCodeCourse  YouTubeCodingTrain  YouTubeCodingTut360  \\\n",
       "1728                 NaN                 NaN                  NaN   \n",
       "1755                 NaN                 NaN                  1.0   \n",
       "7989                 NaN                 NaN                  NaN   \n",
       "8126                 NaN                 NaN                  NaN   \n",
       "13398                NaN                 NaN                  NaN   \n",
       "15587                NaN                 NaN                  NaN   \n",
       "\n",
       "       YouTubeComputerphile  YouTubeDerekBanas  YouTubeDevTips  \\\n",
       "1728                    NaN                NaN             NaN   \n",
       "1755                    NaN                NaN             NaN   \n",
       "7989                    NaN                NaN             NaN   \n",
       "8126                    NaN                NaN             NaN   \n",
       "13398                   NaN                NaN             NaN   \n",
       "15587                   NaN                NaN             NaN   \n",
       "\n",
       "       YouTubeEngineeredTruth  YouTubeFCC  YouTubeFunFunFunction  \\\n",
       "1728                      NaN         1.0                    NaN   \n",
       "1755                      NaN         1.0                    NaN   \n",
       "7989                      NaN         1.0                    NaN   \n",
       "8126                      NaN         NaN                    NaN   \n",
       "13398                     NaN         NaN                    NaN   \n",
       "15587                     NaN         NaN                    NaN   \n",
       "\n",
       "       YouTubeGoogleDev  YouTubeLearnCode  YouTubeLevelUpTuts  YouTubeMIT  \\\n",
       "1728                NaN               NaN                 NaN         NaN   \n",
       "1755                NaN               1.0                 NaN         1.0   \n",
       "7989                NaN               NaN                 NaN         NaN   \n",
       "8126                1.0               NaN                 NaN         1.0   \n",
       "13398               NaN               NaN                 NaN         NaN   \n",
       "15587               1.0               1.0                 NaN         1.0   \n",
       "\n",
       "       YouTubeMozillaHacks YouTubeOther  YouTubeSimplilearn  \\\n",
       "1728                   NaN          NaN                 NaN   \n",
       "1755                   NaN          NaN                 NaN   \n",
       "7989                   NaN          NaN                 NaN   \n",
       "8126                   NaN          NaN                 NaN   \n",
       "13398                  NaN          NaN                 NaN   \n",
       "15587                  NaN          NaN                 NaN   \n",
       "\n",
       "       YouTubeTheNewBoston  money_per_month  \n",
       "1728                   NaN      5000.000000  \n",
       "1755                   NaN      3333.333333  \n",
       "7989                   NaN      5000.000000  \n",
       "8126                   1.0      5000.000000  \n",
       "13398                  NaN     10000.000000  \n",
       "15587                  NaN      4166.666667  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspect the extreme outliers for India\n",
    "india_outliers = only_4[\n",
    "    (only_4['CountryLive'] == 'India') & \n",
    "    (only_4['money_per_month'] >= 2500)]\n",
    "india_outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems that neither participant attended a bootcamp. Overall, it's really hard to figure out from the data whether these persons really spent that much money with learning. The actual question of the survey was \"Aside from university tuition, about how much money have you spent on learning to code so far (in US dollars)?\", so they might have misunderstood and thought university tuition is included. It seems safer to remove these two rows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove the outliers for India\n",
    "only_4 = only_4.drop(india_outliers.index) # using the row labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking back at the box plot above, we can also see more extreme outliers for the US (values over \\$6000 per month). Let's examine these participants in more detail."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>AttendedBootcamp</th>\n",
       "      <th>BootcampFinish</th>\n",
       "      <th>BootcampLoanYesNo</th>\n",
       "      <th>BootcampName</th>\n",
       "      <th>BootcampRecommend</th>\n",
       "      <th>ChildrenNumber</th>\n",
       "      <th>CityPopulation</th>\n",
       "      <th>CodeEventConferences</th>\n",
       "      <th>CodeEventDjangoGirls</th>\n",
       "      <th>CodeEventFCC</th>\n",
       "      <th>CodeEventGameJam</th>\n",
       "      <th>CodeEventGirlDev</th>\n",
       "      <th>CodeEventHackathons</th>\n",
       "      <th>CodeEventMeetup</th>\n",
       "      <th>CodeEventNodeSchool</th>\n",
       "      <th>CodeEventNone</th>\n",
       "      <th>CodeEventOther</th>\n",
       "      <th>CodeEventRailsBridge</th>\n",
       "      <th>CodeEventRailsGirls</th>\n",
       "      <th>CodeEventStartUpWknd</th>\n",
       "      <th>CodeEventWkdBootcamps</th>\n",
       "      <th>CodeEventWomenCode</th>\n",
       "      <th>CodeEventWorkshops</th>\n",
       "      <th>CommuteTime</th>\n",
       "      <th>CountryCitizen</th>\n",
       "      <th>CountryLive</th>\n",
       "      <th>EmploymentField</th>\n",
       "      <th>EmploymentFieldOther</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>EmploymentStatusOther</th>\n",
       "      <th>ExpectedEarning</th>\n",
       "      <th>FinanciallySupporting</th>\n",
       "      <th>FirstDevJob</th>\n",
       "      <th>Gender</th>\n",
       "      <th>GenderOther</th>\n",
       "      <th>HasChildren</th>\n",
       "      <th>HasDebt</th>\n",
       "      <th>HasFinancialDependents</th>\n",
       "      <th>HasHighSpdInternet</th>\n",
       "      <th>HasHomeMortgage</th>\n",
       "      <th>HasServedInMilitary</th>\n",
       "      <th>HasStudentDebt</th>\n",
       "      <th>HomeMortgageOwe</th>\n",
       "      <th>HoursLearning</th>\n",
       "      <th>ID.x</th>\n",
       "      <th>ID.y</th>\n",
       "      <th>Income</th>\n",
       "      <th>IsEthnicMinority</th>\n",
       "      <th>IsReceiveDisabilitiesBenefits</th>\n",
       "      <th>IsSoftwareDev</th>\n",
       "      <th>IsUnderEmployed</th>\n",
       "      <th>JobApplyWhen</th>\n",
       "      <th>JobInterestBackEnd</th>\n",
       "      <th>JobInterestDataEngr</th>\n",
       "      <th>JobInterestDataSci</th>\n",
       "      <th>JobInterestDevOps</th>\n",
       "      <th>JobInterestFrontEnd</th>\n",
       "      <th>JobInterestFullStack</th>\n",
       "      <th>JobInterestGameDev</th>\n",
       "      <th>JobInterestInfoSec</th>\n",
       "      <th>JobInterestMobile</th>\n",
       "      <th>JobInterestOther</th>\n",
       "      <th>JobInterestProjMngr</th>\n",
       "      <th>JobInterestQAEngr</th>\n",
       "      <th>JobInterestUX</th>\n",
       "      <th>JobPref</th>\n",
       "      <th>JobRelocateYesNo</th>\n",
       "      <th>JobRoleInterest</th>\n",
       "      <th>JobWherePref</th>\n",
       "      <th>LanguageAtHome</th>\n",
       "      <th>MaritalStatus</th>\n",
       "      <th>MoneyForLearning</th>\n",
       "      <th>MonthsProgramming</th>\n",
       "      <th>NetworkID</th>\n",
       "      <th>Part1EndTime</th>\n",
       "      <th>Part1StartTime</th>\n",
       "      <th>Part2EndTime</th>\n",
       "      <th>Part2StartTime</th>\n",
       "      <th>PodcastChangeLog</th>\n",
       "      <th>PodcastCodeNewbie</th>\n",
       "      <th>PodcastCodePen</th>\n",
       "      <th>PodcastDevTea</th>\n",
       "      <th>PodcastDotNET</th>\n",
       "      <th>PodcastGiantRobots</th>\n",
       "      <th>PodcastJSAir</th>\n",
       "      <th>PodcastJSJabber</th>\n",
       "      <th>PodcastNone</th>\n",
       "      <th>PodcastOther</th>\n",
       "      <th>PodcastProgThrowdown</th>\n",
       "      <th>PodcastRubyRogues</th>\n",
       "      <th>PodcastSEDaily</th>\n",
       "      <th>PodcastSERadio</th>\n",
       "      <th>PodcastShopTalk</th>\n",
       "      <th>PodcastTalkPython</th>\n",
       "      <th>PodcastTheWebAhead</th>\n",
       "      <th>ResourceCodecademy</th>\n",
       "      <th>ResourceCodeWars</th>\n",
       "      <th>ResourceCoursera</th>\n",
       "      <th>ResourceCSS</th>\n",
       "      <th>ResourceEdX</th>\n",
       "      <th>ResourceEgghead</th>\n",
       "      <th>ResourceFCC</th>\n",
       "      <th>ResourceHackerRank</th>\n",
       "      <th>ResourceKA</th>\n",
       "      <th>ResourceLynda</th>\n",
       "      <th>ResourceMDN</th>\n",
       "      <th>ResourceOdinProj</th>\n",
       "      <th>ResourceOther</th>\n",
       "      <th>ResourcePluralSight</th>\n",
       "      <th>ResourceSkillcrush</th>\n",
       "      <th>ResourceSO</th>\n",
       "      <th>ResourceTreehouse</th>\n",
       "      <th>ResourceUdacity</th>\n",
       "      <th>ResourceUdemy</th>\n",
       "      <th>ResourceW3S</th>\n",
       "      <th>SchoolDegree</th>\n",
       "      <th>SchoolMajor</th>\n",
       "      <th>StudentDebtOwe</th>\n",
       "      <th>YouTubeCodeCourse</th>\n",
       "      <th>YouTubeCodingTrain</th>\n",
       "      <th>YouTubeCodingTut360</th>\n",
       "      <th>YouTubeComputerphile</th>\n",
       "      <th>YouTubeDerekBanas</th>\n",
       "      <th>YouTubeDevTips</th>\n",
       "      <th>YouTubeEngineeredTruth</th>\n",
       "      <th>YouTubeFCC</th>\n",
       "      <th>YouTubeFunFunFunction</th>\n",
       "      <th>YouTubeGoogleDev</th>\n",
       "      <th>YouTubeLearnCode</th>\n",
       "      <th>YouTubeLevelUpTuts</th>\n",
       "      <th>YouTubeMIT</th>\n",
       "      <th>YouTubeMozillaHacks</th>\n",
       "      <th>YouTubeOther</th>\n",
       "      <th>YouTubeSimplilearn</th>\n",
       "      <th>YouTubeTheNewBoston</th>\n",
       "      <th>money_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>718</th>\n",
       "      <td>26.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>The Coding Boot Camp at UCLA Extension</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15 to 29 minutes</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>architecture or physical engineering</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.0</td>\n",
       "      <td>796ae14c2acdee36eebc250a252abdaf</td>\n",
       "      <td>d9e44d73057fa5d322a071adc744bf07</td>\n",
       "      <td>44500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Within the next 6 months</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>work for a startup</td>\n",
       "      <td>1.0</td>\n",
       "      <td>User Experience Designer, Full-Stack Web Dev...</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>English</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50dab3f716</td>\n",
       "      <td>2017-03-09 21:26:35</td>\n",
       "      <td>2017-03-09 21:21:58</td>\n",
       "      <td>2017-03-09 21:29:10</td>\n",
       "      <td>2017-03-09 21:26:39</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Architecture</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1222</th>\n",
       "      <td>32.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>The Iron Yard</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>between 100,000 and 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not working and not looking for work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>bfabebb4293ac002d26a1397d00c7443</td>\n",
       "      <td>590f0be70e80f1daf5a23eb7f4a72a3d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Within the next 6 months</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>work for a nonprofit</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Front-End Web Developer,   Mobile Developer,...</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>English</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>e512c4bdd0</td>\n",
       "      <td>2017-03-10 02:14:11</td>\n",
       "      <td>2017-03-10 02:10:07</td>\n",
       "      <td>2017-03-10 02:15:32</td>\n",
       "      <td>2017-03-10 02:14:16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Anthropology</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6500.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3184</th>\n",
       "      <td>34.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>We Can Code IT</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Less than 15 minutes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>software development and IT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5d4889491d9d25a255e57fd1c0022458</td>\n",
       "      <td>585e8f8b9a838ef1abbe8c6f1891c048</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>I haven't decided</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>work for a medium-sized company</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Quality Assurance Engineer,   DevOps / SysAd...</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>English</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>9000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>e7bebaabd4</td>\n",
       "      <td>2017-03-11 23:34:16</td>\n",
       "      <td>2017-03-11 23:31:17</td>\n",
       "      <td>2017-03-11 23:36:02</td>\n",
       "      <td>2017-03-11 23:34:21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>some college credit, no degree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3930</th>\n",
       "      <td>31.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>between 100,000 and 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not working and not looking for work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>e1d790033545934fbe5bb5b60e368cd9</td>\n",
       "      <td>7cf1e41682462c42ce48029abf77d43c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Within the next 6 months</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a startup</td>\n",
       "      <td>1.0</td>\n",
       "      <td>DevOps / SysAdmin,   Front-End Web Developer...</td>\n",
       "      <td>no preference</td>\n",
       "      <td>English</td>\n",
       "      <td>married or domestic partnership</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>75759e5a1c</td>\n",
       "      <td>2017-03-13 10:06:46</td>\n",
       "      <td>2017-03-13 09:56:13</td>\n",
       "      <td>2017-03-13 10:10:00</td>\n",
       "      <td>2017-03-13 10:06:50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>reactivex.io/learnrx/ &amp; jafar husain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Biology</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>various conf presentations</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10833.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6805</th>\n",
       "      <td>46.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Sabio.la</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>between 100,000 and 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not working but looking for work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.0</td>\n",
       "      <td>69096aacf4245694303cf8f7ce68a63f</td>\n",
       "      <td>4c56f82a348836e76dd90d18a3d5ed88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Within the next 6 months</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a multinational corporation</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Full-Stack Web Developer, Game Developer,   Pr...</td>\n",
       "      <td>no preference</td>\n",
       "      <td>English</td>\n",
       "      <td>married or domestic partnership</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>53d13b58e9</td>\n",
       "      <td>2017-03-21 20:13:08</td>\n",
       "      <td>2017-03-21 20:10:25</td>\n",
       "      <td>2017-03-21 20:14:36</td>\n",
       "      <td>2017-03-21 20:13:11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Business Administration and Management</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7198</th>\n",
       "      <td>32.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15 to 29 minutes</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>education</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>cb2754165344e6be79da8a4c76bf3917</td>\n",
       "      <td>272219fbd28a3a7562cb1d778e482e1e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>I'm already applying</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a multinational corporation</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Full-Stack Web Developer, Back-End Web Developer</td>\n",
       "      <td>no preference</td>\n",
       "      <td>Spanish</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>439a4adaf6</td>\n",
       "      <td>2017-03-23 01:37:46</td>\n",
       "      <td>2017-03-23 01:35:01</td>\n",
       "      <td>2017-03-23 01:39:37</td>\n",
       "      <td>2017-03-23 01:37:49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>professional degree (MBA, MD, JD, etc.)</td>\n",
       "      <td>Computer Science</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7505</th>\n",
       "      <td>26.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Codeup</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not working but looking for work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.0</td>\n",
       "      <td>657fb50800bcc99a07caf52387f67fbb</td>\n",
       "      <td>ad1df4669883d8f628f0b5598a4c5c45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Within the next 6 months</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a government</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Mobile Developer, Full-Stack Web Developer, ...</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>English</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>96e254de36</td>\n",
       "      <td>2017-03-24 03:26:09</td>\n",
       "      <td>2017-03-24 03:23:02</td>\n",
       "      <td>2017-03-24 03:27:47</td>\n",
       "      <td>2017-03-24 03:26:14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Economics</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6666.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9778</th>\n",
       "      <td>33.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Grand Circus</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>between 100,000 and 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15 to 29 minutes</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>education</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.0</td>\n",
       "      <td>7a62790f6ded15e26d5f429b8a4d1095</td>\n",
       "      <td>98eeee1aa81ba70b2ab288bf4b63d703</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Within the next 6 months</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a medium-sized company</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Full-Stack Web Developer, Data Engineer,   Qua...</td>\n",
       "      <td>from home</td>\n",
       "      <td>English</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>ea80a3b15e</td>\n",
       "      <td>2017-04-05 19:48:12</td>\n",
       "      <td>2017-04-05 19:40:19</td>\n",
       "      <td>2017-04-05 19:49:44</td>\n",
       "      <td>2017-04-05 19:49:03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>master's degree (non-professional)</td>\n",
       "      <td>Chemical Engineering</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16650</th>\n",
       "      <td>29.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not working but looking for work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>400000.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>e1925d408c973b91cf3e9a9285238796</td>\n",
       "      <td>7e9e3c31a3dc2cafe3a09269398c4de8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>I'm already applying</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a multinational corporation</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Product Manager, Data Engineer, Full-Stack W...</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>English</td>\n",
       "      <td>married or domestic partnership</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1a45f4a3ef</td>\n",
       "      <td>2017-03-14 02:42:57</td>\n",
       "      <td>2017-03-14 02:40:10</td>\n",
       "      <td>2017-03-14 02:45:55</td>\n",
       "      <td>2017-03-14 02:43:05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>Computer Programming</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16666.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16997</th>\n",
       "      <td>27.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15 to 29 minutes</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>health care</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>624914ce07c296c866c9e16a14dc01c7</td>\n",
       "      <td>6384a1e576caf4b6b9339fe496a51f1f</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Within 7 to 12 months</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>work for a medium-sized company</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Mobile Developer, Game Developer,   User Exp...</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>English</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>12500.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>ad1a21217c</td>\n",
       "      <td>2017-03-20 05:43:28</td>\n",
       "      <td>2017-03-20 05:40:08</td>\n",
       "      <td>2017-03-20 05:45:28</td>\n",
       "      <td>2017-03-20 05:43:32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>some college credit, no degree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12500.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12500.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17231</th>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>less than 100,000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kenya</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not working but looking for work</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>d4bc6ae775b20816fcd41048ef75417c</td>\n",
       "      <td>606749cd07b124234ab6dff81b324c02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Within the next 6 months</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>work for a nonprofit</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Front-End Web Developer</td>\n",
       "      <td>in an office with other developers</td>\n",
       "      <td>English</td>\n",
       "      <td>married or domestic partnership</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>38c1b478d0</td>\n",
       "      <td>2017-03-24 18:48:23</td>\n",
       "      <td>2017-03-24 18:46:01</td>\n",
       "      <td>2017-03-24 18:51:20</td>\n",
       "      <td>2017-03-24 18:48:27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Computer Programming</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15000.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Age  AttendedBootcamp  BootcampFinish  BootcampLoanYesNo  \\\n",
       "718    26.0               1.0             0.0                0.0   \n",
       "1222   32.0               1.0             0.0                0.0   \n",
       "3184   34.0               1.0             1.0                0.0   \n",
       "3930   31.0               0.0             NaN                NaN   \n",
       "6805   46.0               1.0             1.0                1.0   \n",
       "7198   32.0               0.0             NaN                NaN   \n",
       "7505   26.0               1.0             0.0                1.0   \n",
       "9778   33.0               1.0             0.0                1.0   \n",
       "16650  29.0               0.0             NaN                NaN   \n",
       "16997  27.0               0.0             NaN                NaN   \n",
       "17231  50.0               0.0             NaN                NaN   \n",
       "\n",
       "                                 BootcampName  BootcampRecommend  \\\n",
       "718    The Coding Boot Camp at UCLA Extension                1.0   \n",
       "1222                            The Iron Yard                1.0   \n",
       "3184                           We Can Code IT                1.0   \n",
       "3930                                      NaN                NaN   \n",
       "6805                                 Sabio.la                0.0   \n",
       "7198                                      NaN                NaN   \n",
       "7505                                   Codeup                0.0   \n",
       "9778                             Grand Circus                1.0   \n",
       "16650                                     NaN                NaN   \n",
       "16997                                     NaN                NaN   \n",
       "17231                                     NaN                NaN   \n",
       "\n",
       "       ChildrenNumber                 CityPopulation  CodeEventConferences  \\\n",
       "718               NaN            more than 1 million                   1.0   \n",
       "1222              NaN  between 100,000 and 1 million                   NaN   \n",
       "3184              NaN            more than 1 million                   NaN   \n",
       "3930              NaN  between 100,000 and 1 million                   NaN   \n",
       "6805              NaN  between 100,000 and 1 million                   NaN   \n",
       "7198              NaN            more than 1 million                   1.0   \n",
       "7505              NaN            more than 1 million                   NaN   \n",
       "9778              NaN  between 100,000 and 1 million                   NaN   \n",
       "16650             2.0            more than 1 million                   NaN   \n",
       "16997             1.0            more than 1 million                   NaN   \n",
       "17231             2.0              less than 100,000                   NaN   \n",
       "\n",
       "       CodeEventDjangoGirls  CodeEventFCC  CodeEventGameJam  CodeEventGirlDev  \\\n",
       "718                     NaN           NaN               NaN               NaN   \n",
       "1222                    NaN           NaN               NaN               NaN   \n",
       "3184                    NaN           NaN               NaN               NaN   \n",
       "3930                    NaN           NaN               NaN               NaN   \n",
       "6805                    NaN           NaN               NaN               NaN   \n",
       "7198                    NaN           NaN               NaN               NaN   \n",
       "7505                    NaN           NaN               NaN               NaN   \n",
       "9778                    NaN           NaN               NaN               NaN   \n",
       "16650                   NaN           NaN               NaN               NaN   \n",
       "16997                   NaN           NaN               NaN               NaN   \n",
       "17231                   NaN           NaN               NaN               NaN   \n",
       "\n",
       "       CodeEventHackathons  CodeEventMeetup  CodeEventNodeSchool  \\\n",
       "718                    NaN              NaN                  NaN   \n",
       "1222                   NaN              1.0                  NaN   \n",
       "3184                   NaN              1.0                  NaN   \n",
       "3930                   NaN              NaN                  NaN   \n",
       "6805                   NaN              NaN                  NaN   \n",
       "7198                   NaN              1.0                  NaN   \n",
       "7505                   NaN              NaN                  NaN   \n",
       "9778                   NaN              1.0                  NaN   \n",
       "16650                  NaN              1.0                  NaN   \n",
       "16997                  NaN              NaN                  NaN   \n",
       "17231                  NaN              NaN                  NaN   \n",
       "\n",
       "       CodeEventNone CodeEventOther  CodeEventRailsBridge  \\\n",
       "718              NaN            NaN                   NaN   \n",
       "1222             NaN            NaN                   NaN   \n",
       "3184             NaN            NaN                   NaN   \n",
       "3930             NaN            NaN                   NaN   \n",
       "6805             NaN            NaN                   NaN   \n",
       "7198             NaN            NaN                   NaN   \n",
       "7505             NaN            NaN                   NaN   \n",
       "9778             NaN            NaN                   NaN   \n",
       "16650            NaN            NaN                   NaN   \n",
       "16997            NaN            NaN                   NaN   \n",
       "17231            NaN            NaN                   NaN   \n",
       "\n",
       "       CodeEventRailsGirls  CodeEventStartUpWknd  CodeEventWkdBootcamps  \\\n",
       "718                    NaN                   NaN                    NaN   \n",
       "1222                   NaN                   NaN                    NaN   \n",
       "3184                   NaN                   NaN                    NaN   \n",
       "3930                   NaN                   NaN                    NaN   \n",
       "6805                   NaN                   NaN                    NaN   \n",
       "7198                   NaN                   NaN                    NaN   \n",
       "7505                   NaN                   1.0                    NaN   \n",
       "9778                   NaN                   NaN                    NaN   \n",
       "16650                  NaN                   NaN                    NaN   \n",
       "16997                  NaN                   NaN                    NaN   \n",
       "17231                  NaN                   NaN                    NaN   \n",
       "\n",
       "       CodeEventWomenCode  CodeEventWorkshops           CommuteTime  \\\n",
       "718                   NaN                 NaN      15 to 29 minutes   \n",
       "1222                  NaN                 NaN                   NaN   \n",
       "3184                  NaN                 NaN  Less than 15 minutes   \n",
       "3930                  NaN                 NaN                   NaN   \n",
       "6805                  NaN                 NaN                   NaN   \n",
       "7198                  NaN                 NaN      15 to 29 minutes   \n",
       "7505                  NaN                 NaN                   NaN   \n",
       "9778                  NaN                 NaN      15 to 29 minutes   \n",
       "16650                 NaN                 NaN                   NaN   \n",
       "16997                 NaN                 NaN      15 to 29 minutes   \n",
       "17231                 1.0                 NaN                   NaN   \n",
       "\n",
       "                 CountryCitizen               CountryLive  \\\n",
       "718    United States of America  United States of America   \n",
       "1222   United States of America  United States of America   \n",
       "3184                        NaN  United States of America   \n",
       "3930   United States of America  United States of America   \n",
       "6805   United States of America  United States of America   \n",
       "7198   United States of America  United States of America   \n",
       "7505   United States of America  United States of America   \n",
       "9778   United States of America  United States of America   \n",
       "16650  United States of America  United States of America   \n",
       "16997  United States of America  United States of America   \n",
       "17231                     Kenya  United States of America   \n",
       "\n",
       "                            EmploymentField EmploymentFieldOther  \\\n",
       "718    architecture or physical engineering                  NaN   \n",
       "1222                                    NaN                  NaN   \n",
       "3184            software development and IT                  NaN   \n",
       "3930                                    NaN                  NaN   \n",
       "6805                                    NaN                  NaN   \n",
       "7198                              education                  NaN   \n",
       "7505                                    NaN                  NaN   \n",
       "9778                              education                  NaN   \n",
       "16650                                   NaN                  NaN   \n",
       "16997                           health care                  NaN   \n",
       "17231                                   NaN                  NaN   \n",
       "\n",
       "                           EmploymentStatus EmploymentStatusOther  \\\n",
       "718                      Employed for wages                   NaN   \n",
       "1222   Not working and not looking for work                   NaN   \n",
       "3184                     Employed for wages                   NaN   \n",
       "3930   Not working and not looking for work                   NaN   \n",
       "6805       Not working but looking for work                   NaN   \n",
       "7198                     Employed for wages                   NaN   \n",
       "7505       Not working but looking for work                   NaN   \n",
       "9778                     Employed for wages                   NaN   \n",
       "16650      Not working but looking for work                   NaN   \n",
       "16997                    Employed for wages                   NaN   \n",
       "17231      Not working but looking for work                   NaN   \n",
       "\n",
       "       ExpectedEarning  FinanciallySupporting  FirstDevJob  Gender  \\\n",
       "718            50000.0                    NaN          NaN    male   \n",
       "1222           50000.0                    NaN          NaN  female   \n",
       "3184           60000.0                    NaN          NaN    male   \n",
       "3930          100000.0                    NaN          NaN    male   \n",
       "6805           70000.0                    NaN          NaN    male   \n",
       "7198           55000.0                    NaN          NaN    male   \n",
       "7505           65000.0                    NaN          NaN    male   \n",
       "9778           55000.0                    NaN          NaN    male   \n",
       "16650              NaN                    1.0          NaN    male   \n",
       "16997          60000.0                    0.0          NaN  female   \n",
       "17231          40000.0                    0.0          NaN  female   \n",
       "\n",
       "      GenderOther  HasChildren  HasDebt  HasFinancialDependents  \\\n",
       "718           NaN          NaN      0.0                     0.0   \n",
       "1222          NaN          NaN      1.0                     0.0   \n",
       "3184          NaN          NaN      0.0                     0.0   \n",
       "3930          NaN          NaN      1.0                     0.0   \n",
       "6805          NaN          NaN      1.0                     0.0   \n",
       "7198          NaN          NaN      1.0                     0.0   \n",
       "7505          NaN          NaN      1.0                     0.0   \n",
       "9778          NaN          NaN      1.0                     0.0   \n",
       "16650         NaN          1.0      1.0                     1.0   \n",
       "16997         NaN          1.0      1.0                     1.0   \n",
       "17231         NaN          1.0      0.0                     1.0   \n",
       "\n",
       "       HasHighSpdInternet  HasHomeMortgage  HasServedInMilitary  \\\n",
       "718                   0.0              NaN                  0.0   \n",
       "1222                  1.0              0.0                  0.0   \n",
       "3184                  1.0              NaN                  0.0   \n",
       "3930                  1.0              0.0                  0.0   \n",
       "6805                  1.0              0.0                  0.0   \n",
       "7198                  1.0              0.0                  0.0   \n",
       "7505                  1.0              0.0                  0.0   \n",
       "9778                  1.0              0.0                  0.0   \n",
       "16650                 1.0              1.0                  0.0   \n",
       "16997                 1.0              0.0                  0.0   \n",
       "17231                 1.0              NaN                  0.0   \n",
       "\n",
       "       HasStudentDebt  HomeMortgageOwe  HoursLearning  \\\n",
       "718               NaN              NaN           35.0   \n",
       "1222              0.0              NaN           50.0   \n",
       "3184              NaN              NaN           10.0   \n",
       "3930              1.0              NaN           50.0   \n",
       "6805              1.0              NaN           45.0   \n",
       "7198              1.0              NaN            4.0   \n",
       "7505              1.0              NaN           40.0   \n",
       "9778              1.0              NaN           40.0   \n",
       "16650             1.0         400000.0           40.0   \n",
       "16997             1.0              NaN           12.0   \n",
       "17231             NaN              NaN            1.0   \n",
       "\n",
       "                                   ID.x                              ID.y  \\\n",
       "718    796ae14c2acdee36eebc250a252abdaf  d9e44d73057fa5d322a071adc744bf07   \n",
       "1222   bfabebb4293ac002d26a1397d00c7443  590f0be70e80f1daf5a23eb7f4a72a3d   \n",
       "3184   5d4889491d9d25a255e57fd1c0022458  585e8f8b9a838ef1abbe8c6f1891c048   \n",
       "3930   e1d790033545934fbe5bb5b60e368cd9  7cf1e41682462c42ce48029abf77d43c   \n",
       "6805   69096aacf4245694303cf8f7ce68a63f  4c56f82a348836e76dd90d18a3d5ed88   \n",
       "7198   cb2754165344e6be79da8a4c76bf3917  272219fbd28a3a7562cb1d778e482e1e   \n",
       "7505   657fb50800bcc99a07caf52387f67fbb  ad1df4669883d8f628f0b5598a4c5c45   \n",
       "9778   7a62790f6ded15e26d5f429b8a4d1095  98eeee1aa81ba70b2ab288bf4b63d703   \n",
       "16650  e1925d408c973b91cf3e9a9285238796  7e9e3c31a3dc2cafe3a09269398c4de8   \n",
       "16997  624914ce07c296c866c9e16a14dc01c7  6384a1e576caf4b6b9339fe496a51f1f   \n",
       "17231  d4bc6ae775b20816fcd41048ef75417c  606749cd07b124234ab6dff81b324c02   \n",
       "\n",
       "        Income  IsEthnicMinority  IsReceiveDisabilitiesBenefits  \\\n",
       "718    44500.0               0.0                            0.0   \n",
       "1222       NaN               0.0                            0.0   \n",
       "3184   40000.0               0.0                            0.0   \n",
       "3930       NaN               1.0                            0.0   \n",
       "6805       NaN               1.0                            0.0   \n",
       "7198       NaN               1.0                            0.0   \n",
       "7505       NaN               0.0                            0.0   \n",
       "9778   20000.0               0.0                            0.0   \n",
       "16650      NaN               1.0                            1.0   \n",
       "16997  40000.0               1.0                            0.0   \n",
       "17231      NaN               1.0                            0.0   \n",
       "\n",
       "       IsSoftwareDev  IsUnderEmployed              JobApplyWhen  \\\n",
       "718              0.0              1.0  Within the next 6 months   \n",
       "1222             0.0              NaN  Within the next 6 months   \n",
       "3184             0.0              0.0         I haven't decided   \n",
       "3930             0.0              NaN  Within the next 6 months   \n",
       "6805             0.0              NaN  Within the next 6 months   \n",
       "7198             0.0              0.0      I'm already applying   \n",
       "7505             0.0              NaN  Within the next 6 months   \n",
       "9778             0.0              1.0  Within the next 6 months   \n",
       "16650            0.0              NaN      I'm already applying   \n",
       "16997            0.0              0.0     Within 7 to 12 months   \n",
       "17231            0.0              NaN  Within the next 6 months   \n",
       "\n",
       "       JobInterestBackEnd  JobInterestDataEngr  JobInterestDataSci  \\\n",
       "718                   1.0                  NaN                 NaN   \n",
       "1222                  NaN                  NaN                 NaN   \n",
       "3184                  NaN                  1.0                 1.0   \n",
       "3930                  1.0                  NaN                 NaN   \n",
       "6805                  NaN                  1.0                 1.0   \n",
       "7198                  1.0                  NaN                 NaN   \n",
       "7505                  1.0                  NaN                 NaN   \n",
       "9778                  1.0                  1.0                 1.0   \n",
       "16650                 1.0                  1.0                 NaN   \n",
       "16997                 NaN                  NaN                 NaN   \n",
       "17231                 NaN                  NaN                 NaN   \n",
       "\n",
       "       JobInterestDevOps  JobInterestFrontEnd  JobInterestFullStack  \\\n",
       "718                  NaN                  1.0                   1.0   \n",
       "1222                 NaN                  1.0                   NaN   \n",
       "3184                 1.0                  NaN                   NaN   \n",
       "3930                 1.0                  1.0                   1.0   \n",
       "6805                 NaN                  NaN                   1.0   \n",
       "7198                 NaN                  NaN                   1.0   \n",
       "7505                 NaN                  1.0                   1.0   \n",
       "9778                 NaN                  NaN                   1.0   \n",
       "16650                NaN                  1.0                   1.0   \n",
       "16997                NaN                  1.0                   1.0   \n",
       "17231                NaN                  1.0                   NaN   \n",
       "\n",
       "       JobInterestGameDev  JobInterestInfoSec  JobInterestMobile  \\\n",
       "718                   NaN                 NaN                1.0   \n",
       "1222                  NaN                 NaN                1.0   \n",
       "3184                  NaN                 1.0                NaN   \n",
       "3930                  NaN                 NaN                NaN   \n",
       "6805                  1.0                 NaN                NaN   \n",
       "7198                  NaN                 NaN                NaN   \n",
       "7505                  NaN                 1.0                1.0   \n",
       "9778                  NaN                 NaN                1.0   \n",
       "16650                 1.0                 NaN                NaN   \n",
       "16997                 1.0                 NaN                1.0   \n",
       "17231                 NaN                 NaN                NaN   \n",
       "\n",
       "      JobInterestOther  JobInterestProjMngr  JobInterestQAEngr  JobInterestUX  \\\n",
       "718                NaN                  NaN                NaN            1.0   \n",
       "1222               NaN                  NaN                NaN            1.0   \n",
       "3184               NaN                  NaN                1.0            1.0   \n",
       "3930               NaN                  NaN                NaN            NaN   \n",
       "6805               NaN                  1.0                NaN            NaN   \n",
       "7198               NaN                  NaN                NaN            NaN   \n",
       "7505               NaN                  NaN                NaN            NaN   \n",
       "9778               NaN                  NaN                1.0            NaN   \n",
       "16650              NaN                  1.0                NaN            NaN   \n",
       "16997              NaN                  1.0                NaN            1.0   \n",
       "17231              NaN                  NaN                NaN            NaN   \n",
       "\n",
       "                                    JobPref  JobRelocateYesNo  \\\n",
       "718                      work for a startup               1.0   \n",
       "1222                   work for a nonprofit               1.0   \n",
       "3184        work for a medium-sized company               0.0   \n",
       "3930                     work for a startup               1.0   \n",
       "6805   work for a multinational corporation               1.0   \n",
       "7198   work for a multinational corporation               0.0   \n",
       "7505                  work for a government               1.0   \n",
       "9778        work for a medium-sized company               NaN   \n",
       "16650  work for a multinational corporation               1.0   \n",
       "16997       work for a medium-sized company               1.0   \n",
       "17231                  work for a nonprofit               0.0   \n",
       "\n",
       "                                         JobRoleInterest  \\\n",
       "718      User Experience Designer, Full-Stack Web Dev...   \n",
       "1222     Front-End Web Developer,   Mobile Developer,...   \n",
       "3184     Quality Assurance Engineer,   DevOps / SysAd...   \n",
       "3930     DevOps / SysAdmin,   Front-End Web Developer...   \n",
       "6805   Full-Stack Web Developer, Game Developer,   Pr...   \n",
       "7198    Full-Stack Web Developer, Back-End Web Developer   \n",
       "7505     Mobile Developer, Full-Stack Web Developer, ...   \n",
       "9778   Full-Stack Web Developer, Data Engineer,   Qua...   \n",
       "16650    Product Manager, Data Engineer, Full-Stack W...   \n",
       "16997    Mobile Developer, Game Developer,   User Exp...   \n",
       "17231                            Front-End Web Developer   \n",
       "\n",
       "                             JobWherePref LanguageAtHome  \\\n",
       "718    in an office with other developers        English   \n",
       "1222   in an office with other developers        English   \n",
       "3184   in an office with other developers        English   \n",
       "3930                        no preference        English   \n",
       "6805                        no preference        English   \n",
       "7198                        no preference        Spanish   \n",
       "7505   in an office with other developers        English   \n",
       "9778                            from home        English   \n",
       "16650  in an office with other developers        English   \n",
       "16997  in an office with other developers        English   \n",
       "17231  in an office with other developers        English   \n",
       "\n",
       "                         MaritalStatus  MoneyForLearning  MonthsProgramming  \\\n",
       "718              single, never married            8000.0                1.0   \n",
       "1222             single, never married           13000.0                2.0   \n",
       "3184             single, never married            9000.0                1.0   \n",
       "3930   married or domestic partnership           65000.0                6.0   \n",
       "6805   married or domestic partnership           15000.0                1.0   \n",
       "7198             single, never married           70000.0                5.0   \n",
       "7505             single, never married           20000.0                3.0   \n",
       "9778             single, never married            8000.0                1.0   \n",
       "16650  married or domestic partnership          200000.0               12.0   \n",
       "16997            single, never married           12500.0                1.0   \n",
       "17231  married or domestic partnership           30000.0                2.0   \n",
       "\n",
       "        NetworkID         Part1EndTime       Part1StartTime  \\\n",
       "718    50dab3f716  2017-03-09 21:26:35  2017-03-09 21:21:58   \n",
       "1222   e512c4bdd0  2017-03-10 02:14:11  2017-03-10 02:10:07   \n",
       "3184   e7bebaabd4  2017-03-11 23:34:16  2017-03-11 23:31:17   \n",
       "3930   75759e5a1c  2017-03-13 10:06:46  2017-03-13 09:56:13   \n",
       "6805   53d13b58e9  2017-03-21 20:13:08  2017-03-21 20:10:25   \n",
       "7198   439a4adaf6  2017-03-23 01:37:46  2017-03-23 01:35:01   \n",
       "7505   96e254de36  2017-03-24 03:26:09  2017-03-24 03:23:02   \n",
       "9778   ea80a3b15e  2017-04-05 19:48:12  2017-04-05 19:40:19   \n",
       "16650  1a45f4a3ef  2017-03-14 02:42:57  2017-03-14 02:40:10   \n",
       "16997  ad1a21217c  2017-03-20 05:43:28  2017-03-20 05:40:08   \n",
       "17231  38c1b478d0  2017-03-24 18:48:23  2017-03-24 18:46:01   \n",
       "\n",
       "              Part2EndTime       Part2StartTime  PodcastChangeLog  \\\n",
       "718    2017-03-09 21:29:10  2017-03-09 21:26:39               NaN   \n",
       "1222   2017-03-10 02:15:32  2017-03-10 02:14:16               NaN   \n",
       "3184   2017-03-11 23:36:02  2017-03-11 23:34:21               NaN   \n",
       "3930   2017-03-13 10:10:00  2017-03-13 10:06:50               NaN   \n",
       "6805   2017-03-21 20:14:36  2017-03-21 20:13:11               NaN   \n",
       "7198   2017-03-23 01:39:37  2017-03-23 01:37:49               NaN   \n",
       "7505   2017-03-24 03:27:47  2017-03-24 03:26:14               NaN   \n",
       "9778   2017-04-05 19:49:44  2017-04-05 19:49:03               NaN   \n",
       "16650  2017-03-14 02:45:55  2017-03-14 02:43:05               NaN   \n",
       "16997  2017-03-20 05:45:28  2017-03-20 05:43:32               NaN   \n",
       "17231  2017-03-24 18:51:20  2017-03-24 18:48:27               NaN   \n",
       "\n",
       "       PodcastCodeNewbie  PodcastCodePen  PodcastDevTea  PodcastDotNET  \\\n",
       "718                  1.0             1.0            NaN            NaN   \n",
       "1222                 NaN             NaN            NaN            NaN   \n",
       "3184                 1.0             NaN            NaN            NaN   \n",
       "3930                 NaN             NaN            NaN            NaN   \n",
       "6805                 NaN             NaN            NaN            NaN   \n",
       "7198                 NaN             NaN            NaN            NaN   \n",
       "7505                 NaN             NaN            1.0            NaN   \n",
       "9778                 NaN             NaN            NaN            NaN   \n",
       "16650                NaN             NaN            NaN            NaN   \n",
       "16997                NaN             NaN            NaN            NaN   \n",
       "17231                NaN             NaN            NaN            NaN   \n",
       "\n",
       "       PodcastGiantRobots  PodcastJSAir  PodcastJSJabber  PodcastNone  \\\n",
       "718                   NaN           NaN              NaN          NaN   \n",
       "1222                  NaN           NaN              1.0          NaN   \n",
       "3184                  NaN           NaN              NaN          NaN   \n",
       "3930                  NaN           1.0              1.0          NaN   \n",
       "6805                  NaN           NaN              NaN          NaN   \n",
       "7198                  NaN           NaN              NaN          NaN   \n",
       "7505                  NaN           NaN              NaN          NaN   \n",
       "9778                  NaN           NaN              NaN          NaN   \n",
       "16650                 NaN           NaN              NaN          NaN   \n",
       "16997                 NaN           NaN              NaN          NaN   \n",
       "17231                 NaN           NaN              NaN          NaN   \n",
       "\n",
       "      PodcastOther  PodcastProgThrowdown  PodcastRubyRogues  PodcastSEDaily  \\\n",
       "718            NaN                   NaN                NaN             1.0   \n",
       "1222           NaN                   NaN                NaN             NaN   \n",
       "3184           NaN                   NaN                NaN             1.0   \n",
       "3930           NaN                   NaN                NaN             NaN   \n",
       "6805           NaN                   NaN                NaN             NaN   \n",
       "7198           NaN                   NaN                NaN             NaN   \n",
       "7505           NaN                   NaN                NaN             NaN   \n",
       "9778           NaN                   NaN                NaN             NaN   \n",
       "16650          NaN                   NaN                NaN             NaN   \n",
       "16997          NaN                   NaN                NaN             NaN   \n",
       "17231          NaN                   NaN                NaN             1.0   \n",
       "\n",
       "       PodcastSERadio  PodcastShopTalk  PodcastTalkPython  PodcastTheWebAhead  \\\n",
       "718               NaN              NaN                NaN                 NaN   \n",
       "1222              NaN              NaN                NaN                 NaN   \n",
       "3184              NaN              NaN                NaN                 NaN   \n",
       "3930              NaN              NaN                NaN                 NaN   \n",
       "6805              NaN              NaN                NaN                 NaN   \n",
       "7198              NaN              NaN                NaN                 NaN   \n",
       "7505              NaN              NaN                NaN                 NaN   \n",
       "9778              NaN              NaN                NaN                 NaN   \n",
       "16650             NaN              NaN                NaN                 NaN   \n",
       "16997             NaN              NaN                NaN                 NaN   \n",
       "17231             NaN              NaN                NaN                 NaN   \n",
       "\n",
       "       ResourceCodecademy  ResourceCodeWars  ResourceCoursera  ResourceCSS  \\\n",
       "718                   NaN               1.0               NaN          NaN   \n",
       "1222                  1.0               NaN               NaN          1.0   \n",
       "3184                  NaN               1.0               NaN          1.0   \n",
       "3930                  NaN               NaN               NaN          NaN   \n",
       "6805                  1.0               NaN               NaN          NaN   \n",
       "7198                  1.0               NaN               1.0          1.0   \n",
       "7505                  1.0               NaN               NaN          NaN   \n",
       "9778                  NaN               NaN               NaN          NaN   \n",
       "16650                 NaN               NaN               1.0          NaN   \n",
       "16997                 1.0               NaN               NaN          NaN   \n",
       "17231                 NaN               NaN               NaN          NaN   \n",
       "\n",
       "       ResourceEdX  ResourceEgghead  ResourceFCC  ResourceHackerRank  \\\n",
       "718            NaN              NaN          1.0                 NaN   \n",
       "1222           NaN              1.0          1.0                 NaN   \n",
       "3184           NaN              NaN          NaN                 NaN   \n",
       "3930           NaN              1.0          1.0                 NaN   \n",
       "6805           NaN              NaN          1.0                 NaN   \n",
       "7198           NaN              NaN          1.0                 NaN   \n",
       "7505           NaN              NaN          1.0                 NaN   \n",
       "9778           NaN              NaN          1.0                 NaN   \n",
       "16650          NaN              NaN          1.0                 NaN   \n",
       "16997          NaN              NaN          1.0                 NaN   \n",
       "17231          NaN              NaN          NaN                 NaN   \n",
       "\n",
       "       ResourceKA  ResourceLynda  ResourceMDN  ResourceOdinProj  \\\n",
       "718           NaN            NaN          NaN               NaN   \n",
       "1222          NaN            NaN          1.0               NaN   \n",
       "3184          NaN            NaN          NaN               NaN   \n",
       "3930          NaN            NaN          1.0               NaN   \n",
       "6805          NaN            NaN          NaN               NaN   \n",
       "7198          1.0            NaN          1.0               NaN   \n",
       "7505          NaN            1.0          NaN               NaN   \n",
       "9778          NaN            NaN          NaN               NaN   \n",
       "16650         NaN            NaN          NaN               NaN   \n",
       "16997         NaN            NaN          NaN               NaN   \n",
       "17231         NaN            NaN          NaN               NaN   \n",
       "\n",
       "                              ResourceOther  ResourcePluralSight  \\\n",
       "718                                     NaN                  NaN   \n",
       "1222                                    NaN                  1.0   \n",
       "3184                                    NaN                  NaN   \n",
       "3930   reactivex.io/learnrx/ & jafar husain                  NaN   \n",
       "6805                                    NaN                  NaN   \n",
       "7198                                    NaN                  NaN   \n",
       "7505                                    NaN                  1.0   \n",
       "9778                                    NaN                  NaN   \n",
       "16650                                   NaN                  NaN   \n",
       "16997                                   NaN                  NaN   \n",
       "17231                                   NaN                  NaN   \n",
       "\n",
       "       ResourceSkillcrush  ResourceSO  ResourceTreehouse  ResourceUdacity  \\\n",
       "718                   NaN         NaN                NaN              NaN   \n",
       "1222                  1.0         1.0                1.0              1.0   \n",
       "3184                  NaN         1.0                NaN              1.0   \n",
       "3930                  NaN         1.0                NaN              NaN   \n",
       "6805                  NaN         1.0                1.0              1.0   \n",
       "7198                  NaN         1.0                NaN              1.0   \n",
       "7505                  NaN         1.0                NaN              NaN   \n",
       "9778                  NaN         1.0                1.0              1.0   \n",
       "16650                 NaN         NaN                NaN              1.0   \n",
       "16997                 NaN         1.0                NaN              NaN   \n",
       "17231                 NaN         NaN                NaN              NaN   \n",
       "\n",
       "       ResourceUdemy  ResourceW3S                             SchoolDegree  \\\n",
       "718              NaN          NaN                        bachelor's degree   \n",
       "1222             1.0          NaN                        bachelor's degree   \n",
       "3184             1.0          1.0           some college credit, no degree   \n",
       "3930             NaN          NaN                        bachelor's degree   \n",
       "6805             1.0          1.0                        bachelor's degree   \n",
       "7198             NaN          1.0  professional degree (MBA, MD, JD, etc.)   \n",
       "7505             1.0          1.0                        bachelor's degree   \n",
       "9778             NaN          NaN       master's degree (non-professional)   \n",
       "16650            NaN          1.0                       associate's degree   \n",
       "16997            1.0          1.0           some college credit, no degree   \n",
       "17231            1.0          NaN                        bachelor's degree   \n",
       "\n",
       "                                  SchoolMajor  StudentDebtOwe  \\\n",
       "718                              Architecture             NaN   \n",
       "1222                             Anthropology             NaN   \n",
       "3184                                      NaN             NaN   \n",
       "3930                                  Biology         40000.0   \n",
       "6805   Business Administration and Management         45000.0   \n",
       "7198                         Computer Science             NaN   \n",
       "7505                                Economics         20000.0   \n",
       "9778                     Chemical Engineering         45000.0   \n",
       "16650                    Computer Programming         30000.0   \n",
       "16997                                     NaN         12500.0   \n",
       "17231                    Computer Programming             NaN   \n",
       "\n",
       "       YouTubeCodeCourse  YouTubeCodingTrain  YouTubeCodingTut360  \\\n",
       "718                  NaN                 NaN                  NaN   \n",
       "1222                 NaN                 1.0                  NaN   \n",
       "3184                 NaN                 NaN                  NaN   \n",
       "3930                 NaN                 NaN                  NaN   \n",
       "6805                 NaN                 NaN                  NaN   \n",
       "7198                 NaN                 NaN                  NaN   \n",
       "7505                 NaN                 NaN                  NaN   \n",
       "9778                 NaN                 NaN                  NaN   \n",
       "16650                NaN                 NaN                  NaN   \n",
       "16997                NaN                 NaN                  NaN   \n",
       "17231                NaN                 NaN                  NaN   \n",
       "\n",
       "       YouTubeComputerphile  YouTubeDerekBanas  YouTubeDevTips  \\\n",
       "718                     NaN                NaN             NaN   \n",
       "1222                    NaN                NaN             1.0   \n",
       "3184                    NaN                NaN             NaN   \n",
       "3930                    NaN                NaN             NaN   \n",
       "6805                    NaN                NaN             NaN   \n",
       "7198                    NaN                NaN             NaN   \n",
       "7505                    NaN                NaN             NaN   \n",
       "9778                    NaN                NaN             NaN   \n",
       "16650                   NaN                NaN             NaN   \n",
       "16997                   NaN                NaN             NaN   \n",
       "17231                   NaN                1.0             NaN   \n",
       "\n",
       "       YouTubeEngineeredTruth  YouTubeFCC  YouTubeFunFunFunction  \\\n",
       "718                       NaN         1.0                    NaN   \n",
       "1222                      NaN         1.0                    NaN   \n",
       "3184                      NaN         NaN                    NaN   \n",
       "3930                      1.0         1.0                    1.0   \n",
       "6805                      NaN         1.0                    NaN   \n",
       "7198                      NaN         1.0                    NaN   \n",
       "7505                      NaN         NaN                    NaN   \n",
       "9778                      NaN         NaN                    NaN   \n",
       "16650                     NaN         NaN                    NaN   \n",
       "16997                     NaN         NaN                    NaN   \n",
       "17231                     NaN         NaN                    NaN   \n",
       "\n",
       "       YouTubeGoogleDev  YouTubeLearnCode  YouTubeLevelUpTuts  YouTubeMIT  \\\n",
       "718                 NaN               NaN                 NaN         NaN   \n",
       "1222                NaN               1.0                 NaN         NaN   \n",
       "3184                NaN               NaN                 NaN         NaN   \n",
       "3930                1.0               1.0                 1.0         1.0   \n",
       "6805                NaN               NaN                 NaN         NaN   \n",
       "7198                1.0               1.0                 1.0         NaN   \n",
       "7505                NaN               NaN                 NaN         1.0   \n",
       "9778                NaN               NaN                 NaN         NaN   \n",
       "16650               NaN               NaN                 NaN         NaN   \n",
       "16997               NaN               NaN                 NaN         NaN   \n",
       "17231               NaN               NaN                 NaN         NaN   \n",
       "\n",
       "       YouTubeMozillaHacks                YouTubeOther  YouTubeSimplilearn  \\\n",
       "718                    NaN                         NaN                 NaN   \n",
       "1222                   NaN                         NaN                 NaN   \n",
       "3184                   NaN                         NaN                 NaN   \n",
       "3930                   NaN  various conf presentations                 NaN   \n",
       "6805                   NaN                         NaN                 NaN   \n",
       "7198                   NaN                         NaN                 NaN   \n",
       "7505                   NaN                         NaN                 NaN   \n",
       "9778                   NaN                         NaN                 NaN   \n",
       "16650                  NaN                         NaN                 NaN   \n",
       "16997                  NaN                         NaN                 NaN   \n",
       "17231                  NaN                         NaN                 NaN   \n",
       "\n",
       "       YouTubeTheNewBoston  money_per_month  \n",
       "718                    NaN      8000.000000  \n",
       "1222                   NaN      6500.000000  \n",
       "3184                   NaN      9000.000000  \n",
       "3930                   NaN     10833.333333  \n",
       "6805                   NaN     15000.000000  \n",
       "7198                   NaN     14000.000000  \n",
       "7505                   NaN      6666.666667  \n",
       "9778                   NaN      8000.000000  \n",
       "16650                  1.0     16666.666667  \n",
       "16997                  NaN     12500.000000  \n",
       "17231                  NaN     15000.000000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Examine the extreme outliers for the US\n",
    "us_outliers = only_4[\n",
    "    (only_4['CountryLive'] == 'United States of America') & \n",
    "    (only_4['money_per_month'] >= 6000)]\n",
    "\n",
    "us_outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Out of these 11 extreme outliers, six people attended bootcamps, which justify the large sums of money spent on learning. For the other five, it's hard to figure out from the data where they could have spent that much money on learning. Consequently, we'll remove those rows where participants reported thay they spend \\$6000 each month, but they have never attended a bootcamp.\n",
    "\n",
    "Also, the data shows that eight respondents had been programming for no more than three months when they completed the survey. They most likely paid a large sum of money for a bootcamp that was going to last for several months, so the amount of money spent per month is unrealistic and should be significantly lower (because they probably didn't spend anything for the next couple of months after the survey). As a consequence, we'll remove every these eight outliers.\n",
    "\n",
    "In the next code block, we'll remove respondents that:\n",
    "\n",
    "* Didn't attend bootcamps.\n",
    "* Had been programming for three months or less when at the time they completed the survey."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove the respondents who didn't attendent a bootcamp\n",
    "no_bootcamp = only_4[\n",
    "    (only_4['CountryLive'] == 'United States of America') & \n",
    "    (only_4['money_per_month'] >= 6000) &\n",
    "    (only_4['AttendedBootcamp'] == 0)\n",
    "]\n",
    "\n",
    "only_4 = only_4.drop(no_bootcamp.index)\n",
    "\n",
    "\n",
    "# Remove the respondents that had been programming for less than 3 months\n",
    "less_than_3_months = only_4[\n",
    "    (only_4['CountryLive'] == 'United States of America') & \n",
    "    (only_4['money_per_month'] >= 6000) &\n",
    "    (only_4['MonthsProgramming'] <= 3)\n",
    "]\n",
    "\n",
    "only_4 = only_4.drop(less_than_3_months.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking again at the last box plot above, we can also see an extreme outlier for Canada — a person who spends roughly \\$5000 per month. Let's examine this person in more depth."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>AttendedBootcamp</th>\n",
       "      <th>BootcampFinish</th>\n",
       "      <th>BootcampLoanYesNo</th>\n",
       "      <th>BootcampName</th>\n",
       "      <th>BootcampRecommend</th>\n",
       "      <th>ChildrenNumber</th>\n",
       "      <th>CityPopulation</th>\n",
       "      <th>CodeEventConferences</th>\n",
       "      <th>CodeEventDjangoGirls</th>\n",
       "      <th>CodeEventFCC</th>\n",
       "      <th>CodeEventGameJam</th>\n",
       "      <th>CodeEventGirlDev</th>\n",
       "      <th>CodeEventHackathons</th>\n",
       "      <th>CodeEventMeetup</th>\n",
       "      <th>CodeEventNodeSchool</th>\n",
       "      <th>CodeEventNone</th>\n",
       "      <th>CodeEventOther</th>\n",
       "      <th>CodeEventRailsBridge</th>\n",
       "      <th>CodeEventRailsGirls</th>\n",
       "      <th>CodeEventStartUpWknd</th>\n",
       "      <th>CodeEventWkdBootcamps</th>\n",
       "      <th>CodeEventWomenCode</th>\n",
       "      <th>CodeEventWorkshops</th>\n",
       "      <th>CommuteTime</th>\n",
       "      <th>CountryCitizen</th>\n",
       "      <th>CountryLive</th>\n",
       "      <th>EmploymentField</th>\n",
       "      <th>EmploymentFieldOther</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>EmploymentStatusOther</th>\n",
       "      <th>ExpectedEarning</th>\n",
       "      <th>FinanciallySupporting</th>\n",
       "      <th>FirstDevJob</th>\n",
       "      <th>Gender</th>\n",
       "      <th>GenderOther</th>\n",
       "      <th>HasChildren</th>\n",
       "      <th>HasDebt</th>\n",
       "      <th>HasFinancialDependents</th>\n",
       "      <th>HasHighSpdInternet</th>\n",
       "      <th>HasHomeMortgage</th>\n",
       "      <th>HasServedInMilitary</th>\n",
       "      <th>HasStudentDebt</th>\n",
       "      <th>HomeMortgageOwe</th>\n",
       "      <th>HoursLearning</th>\n",
       "      <th>ID.x</th>\n",
       "      <th>ID.y</th>\n",
       "      <th>Income</th>\n",
       "      <th>IsEthnicMinority</th>\n",
       "      <th>IsReceiveDisabilitiesBenefits</th>\n",
       "      <th>IsSoftwareDev</th>\n",
       "      <th>IsUnderEmployed</th>\n",
       "      <th>JobApplyWhen</th>\n",
       "      <th>JobInterestBackEnd</th>\n",
       "      <th>JobInterestDataEngr</th>\n",
       "      <th>JobInterestDataSci</th>\n",
       "      <th>JobInterestDevOps</th>\n",
       "      <th>JobInterestFrontEnd</th>\n",
       "      <th>JobInterestFullStack</th>\n",
       "      <th>JobInterestGameDev</th>\n",
       "      <th>JobInterestInfoSec</th>\n",
       "      <th>JobInterestMobile</th>\n",
       "      <th>JobInterestOther</th>\n",
       "      <th>JobInterestProjMngr</th>\n",
       "      <th>JobInterestQAEngr</th>\n",
       "      <th>JobInterestUX</th>\n",
       "      <th>JobPref</th>\n",
       "      <th>JobRelocateYesNo</th>\n",
       "      <th>JobRoleInterest</th>\n",
       "      <th>JobWherePref</th>\n",
       "      <th>LanguageAtHome</th>\n",
       "      <th>MaritalStatus</th>\n",
       "      <th>MoneyForLearning</th>\n",
       "      <th>MonthsProgramming</th>\n",
       "      <th>NetworkID</th>\n",
       "      <th>Part1EndTime</th>\n",
       "      <th>Part1StartTime</th>\n",
       "      <th>Part2EndTime</th>\n",
       "      <th>Part2StartTime</th>\n",
       "      <th>PodcastChangeLog</th>\n",
       "      <th>PodcastCodeNewbie</th>\n",
       "      <th>PodcastCodePen</th>\n",
       "      <th>PodcastDevTea</th>\n",
       "      <th>PodcastDotNET</th>\n",
       "      <th>PodcastGiantRobots</th>\n",
       "      <th>PodcastJSAir</th>\n",
       "      <th>PodcastJSJabber</th>\n",
       "      <th>PodcastNone</th>\n",
       "      <th>PodcastOther</th>\n",
       "      <th>PodcastProgThrowdown</th>\n",
       "      <th>PodcastRubyRogues</th>\n",
       "      <th>PodcastSEDaily</th>\n",
       "      <th>PodcastSERadio</th>\n",
       "      <th>PodcastShopTalk</th>\n",
       "      <th>PodcastTalkPython</th>\n",
       "      <th>PodcastTheWebAhead</th>\n",
       "      <th>ResourceCodecademy</th>\n",
       "      <th>ResourceCodeWars</th>\n",
       "      <th>ResourceCoursera</th>\n",
       "      <th>ResourceCSS</th>\n",
       "      <th>ResourceEdX</th>\n",
       "      <th>ResourceEgghead</th>\n",
       "      <th>ResourceFCC</th>\n",
       "      <th>ResourceHackerRank</th>\n",
       "      <th>ResourceKA</th>\n",
       "      <th>ResourceLynda</th>\n",
       "      <th>ResourceMDN</th>\n",
       "      <th>ResourceOdinProj</th>\n",
       "      <th>ResourceOther</th>\n",
       "      <th>ResourcePluralSight</th>\n",
       "      <th>ResourceSkillcrush</th>\n",
       "      <th>ResourceSO</th>\n",
       "      <th>ResourceTreehouse</th>\n",
       "      <th>ResourceUdacity</th>\n",
       "      <th>ResourceUdemy</th>\n",
       "      <th>ResourceW3S</th>\n",
       "      <th>SchoolDegree</th>\n",
       "      <th>SchoolMajor</th>\n",
       "      <th>StudentDebtOwe</th>\n",
       "      <th>YouTubeCodeCourse</th>\n",
       "      <th>YouTubeCodingTrain</th>\n",
       "      <th>YouTubeCodingTut360</th>\n",
       "      <th>YouTubeComputerphile</th>\n",
       "      <th>YouTubeDerekBanas</th>\n",
       "      <th>YouTubeDevTips</th>\n",
       "      <th>YouTubeEngineeredTruth</th>\n",
       "      <th>YouTubeFCC</th>\n",
       "      <th>YouTubeFunFunFunction</th>\n",
       "      <th>YouTubeGoogleDev</th>\n",
       "      <th>YouTubeLearnCode</th>\n",
       "      <th>YouTubeLevelUpTuts</th>\n",
       "      <th>YouTubeMIT</th>\n",
       "      <th>YouTubeMozillaHacks</th>\n",
       "      <th>YouTubeOther</th>\n",
       "      <th>YouTubeSimplilearn</th>\n",
       "      <th>YouTubeTheNewBoston</th>\n",
       "      <th>money_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>13659</th>\n",
       "      <td>24.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Bloc.io</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>more than 1 million</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>30 to 44 minutes</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Canada</td>\n",
       "      <td>finance</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>739b584aef0541450c1f713b82025181</td>\n",
       "      <td>28381a455ab25cc2a118d78af44d8749</td>\n",
       "      <td>140000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>I haven't decided</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>work for a multinational corporation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mobile Developer, Full-Stack Web Developer, ...</td>\n",
       "      <td>from home</td>\n",
       "      <td>Yue (Cantonese) Chinese</td>\n",
       "      <td>single, never married</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>41c26f2932</td>\n",
       "      <td>2017-03-25 23:23:03</td>\n",
       "      <td>2017-03-25 23:20:33</td>\n",
       "      <td>2017-03-25 23:24:34</td>\n",
       "      <td>2017-03-25 23:23:06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>Finance</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Age  AttendedBootcamp  BootcampFinish  BootcampLoanYesNo BootcampName  \\\n",
       "13659  24.0               1.0             0.0                0.0      Bloc.io   \n",
       "\n",
       "       BootcampRecommend  ChildrenNumber       CityPopulation  \\\n",
       "13659                1.0             NaN  more than 1 million   \n",
       "\n",
       "       CodeEventConferences  CodeEventDjangoGirls  CodeEventFCC  \\\n",
       "13659                   1.0                   NaN           1.0   \n",
       "\n",
       "       CodeEventGameJam  CodeEventGirlDev  CodeEventHackathons  \\\n",
       "13659               NaN               NaN                  NaN   \n",
       "\n",
       "       CodeEventMeetup  CodeEventNodeSchool  CodeEventNone CodeEventOther  \\\n",
       "13659              1.0                  NaN            NaN            NaN   \n",
       "\n",
       "       CodeEventRailsBridge  CodeEventRailsGirls  CodeEventStartUpWknd  \\\n",
       "13659                   NaN                  NaN                   NaN   \n",
       "\n",
       "       CodeEventWkdBootcamps  CodeEventWomenCode  CodeEventWorkshops  \\\n",
       "13659                    NaN                 NaN                 1.0   \n",
       "\n",
       "            CommuteTime CountryCitizen CountryLive EmploymentField  \\\n",
       "13659  30 to 44 minutes         Canada      Canada         finance   \n",
       "\n",
       "      EmploymentFieldOther    EmploymentStatus EmploymentStatusOther  \\\n",
       "13659                  NaN  Employed for wages                   NaN   \n",
       "\n",
       "       ExpectedEarning  FinanciallySupporting  FirstDevJob Gender GenderOther  \\\n",
       "13659          60000.0                    NaN          NaN   male         NaN   \n",
       "\n",
       "       HasChildren  HasDebt  HasFinancialDependents  HasHighSpdInternet  \\\n",
       "13659          NaN      1.0                     0.0                 1.0   \n",
       "\n",
       "       HasHomeMortgage  HasServedInMilitary  HasStudentDebt  HomeMortgageOwe  \\\n",
       "13659              1.0                  0.0             0.0         250000.0   \n",
       "\n",
       "       HoursLearning                              ID.x  \\\n",
       "13659           10.0  739b584aef0541450c1f713b82025181   \n",
       "\n",
       "                                   ID.y    Income  IsEthnicMinority  \\\n",
       "13659  28381a455ab25cc2a118d78af44d8749  140000.0               1.0   \n",
       "\n",
       "       IsReceiveDisabilitiesBenefits  IsSoftwareDev  IsUnderEmployed  \\\n",
       "13659                            1.0            0.0              0.0   \n",
       "\n",
       "            JobApplyWhen  JobInterestBackEnd  JobInterestDataEngr  \\\n",
       "13659  I haven't decided                 1.0                  NaN   \n",
       "\n",
       "       JobInterestDataSci  JobInterestDevOps  JobInterestFrontEnd  \\\n",
       "13659                 1.0                NaN                  1.0   \n",
       "\n",
       "       JobInterestFullStack  JobInterestGameDev  JobInterestInfoSec  \\\n",
       "13659                   1.0                 1.0                 NaN   \n",
       "\n",
       "       JobInterestMobile JobInterestOther  JobInterestProjMngr  \\\n",
       "13659                1.0              NaN                  1.0   \n",
       "\n",
       "       JobInterestQAEngr  JobInterestUX                               JobPref  \\\n",
       "13659                NaN            1.0  work for a multinational corporation   \n",
       "\n",
       "       JobRelocateYesNo                                    JobRoleInterest  \\\n",
       "13659               NaN    Mobile Developer, Full-Stack Web Developer, ...   \n",
       "\n",
       "      JobWherePref           LanguageAtHome          MaritalStatus  \\\n",
       "13659    from home  Yue (Cantonese) Chinese  single, never married   \n",
       "\n",
       "       MoneyForLearning  MonthsProgramming   NetworkID         Part1EndTime  \\\n",
       "13659           10000.0                2.0  41c26f2932  2017-03-25 23:23:03   \n",
       "\n",
       "            Part1StartTime         Part2EndTime       Part2StartTime  \\\n",
       "13659  2017-03-25 23:20:33  2017-03-25 23:24:34  2017-03-25 23:23:06   \n",
       "\n",
       "       PodcastChangeLog  PodcastCodeNewbie  PodcastCodePen  PodcastDevTea  \\\n",
       "13659               NaN                NaN             NaN            NaN   \n",
       "\n",
       "       PodcastDotNET  PodcastGiantRobots  PodcastJSAir  PodcastJSJabber  \\\n",
       "13659            NaN                 NaN           NaN              NaN   \n",
       "\n",
       "       PodcastNone PodcastOther  PodcastProgThrowdown  PodcastRubyRogues  \\\n",
       "13659          1.0          NaN                   NaN                NaN   \n",
       "\n",
       "       PodcastSEDaily  PodcastSERadio  PodcastShopTalk  PodcastTalkPython  \\\n",
       "13659             NaN             NaN              NaN                NaN   \n",
       "\n",
       "       PodcastTheWebAhead  ResourceCodecademy  ResourceCodeWars  \\\n",
       "13659                 NaN                 1.0               1.0   \n",
       "\n",
       "       ResourceCoursera  ResourceCSS  ResourceEdX  ResourceEgghead  \\\n",
       "13659               1.0          NaN          NaN              NaN   \n",
       "\n",
       "       ResourceFCC  ResourceHackerRank  ResourceKA  ResourceLynda  \\\n",
       "13659          1.0                 NaN         NaN            NaN   \n",
       "\n",
       "       ResourceMDN  ResourceOdinProj ResourceOther  ResourcePluralSight  \\\n",
       "13659          NaN               NaN           NaN                  NaN   \n",
       "\n",
       "       ResourceSkillcrush  ResourceSO  ResourceTreehouse  ResourceUdacity  \\\n",
       "13659                 NaN         1.0                NaN              NaN   \n",
       "\n",
       "       ResourceUdemy  ResourceW3S       SchoolDegree SchoolMajor  \\\n",
       "13659            NaN          1.0  bachelor's degree     Finance   \n",
       "\n",
       "       StudentDebtOwe  YouTubeCodeCourse  YouTubeCodingTrain  \\\n",
       "13659             NaN                NaN                 NaN   \n",
       "\n",
       "       YouTubeCodingTut360  YouTubeComputerphile  YouTubeDerekBanas  \\\n",
       "13659                  NaN                   NaN                NaN   \n",
       "\n",
       "       YouTubeDevTips  YouTubeEngineeredTruth  YouTubeFCC  \\\n",
       "13659             NaN                     NaN         1.0   \n",
       "\n",
       "       YouTubeFunFunFunction  YouTubeGoogleDev  YouTubeLearnCode  \\\n",
       "13659                    NaN               NaN               NaN   \n",
       "\n",
       "       YouTubeLevelUpTuts  YouTubeMIT  YouTubeMozillaHacks YouTubeOther  \\\n",
       "13659                 NaN         1.0                  NaN          NaN   \n",
       "\n",
       "       YouTubeSimplilearn  YouTubeTheNewBoston  money_per_month  \n",
       "13659                 NaN                  NaN           5000.0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Examine the extreme outliers for Canada\n",
    "canada_outliers = only_4[\n",
    "    (only_4['CountryLive'] == 'Canada') & \n",
    "    (only_4['money_per_month'] > 4500)]\n",
    "\n",
    "canada_outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, the situation is similar to some of the US respondents — this participant had been programming for no more than two months when he completed the survey. He seems to have paid a large sum of money in the beginning to enroll in a bootcamp, and then he probably didn't spend anything for the next couple of months after the survey. We'll take the same approach here as for the US and remove this outlier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove the extreme outliers for Canada\n",
    "only_4 = only_4.drop(canada_outliers.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's recompute the mean values and generate the final box plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CountryLive\n",
       "Canada                       93.065400\n",
       "India                        65.758763\n",
       "United Kingdom               45.534443\n",
       "United States of America    142.654608\n",
       "Name: money_per_month, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Recompute mean sum of money spent by students each month\n",
    "only_4.groupby('CountryLive').mean()['money_per_month']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the distributions again\n",
    "sns.boxplot(y = 'money_per_month', x = 'CountryLive',\n",
    "            data = only_4)\n",
    "plt.title('Money Spent Per Month Per Country\\n(Distributions)',\n",
    "          fontsize = 16)\n",
    "plt.ylabel('Money per month (US dollars)')\n",
    "plt.xlabel('Country')\n",
    "plt.xticks(range(4), ['US', 'UK', 'India', 'Canada']) # avoids tick labels overlap\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Choosing the Two Best Markets\n",
    "\n",
    "Obviously, one country we should advertise in is the US. Lots of new coders live there and they are willing to pay a good amount of money each month (roughly per $143).\n",
    "\n",
    "We sell subscriptions at a price of per `$59` per month, and Canada seems to be the best second choice because people there are willing to pay roughly per `$93` per month, compared to India (per `$66`) and the United Kingdom (per `$45`).\n",
    "\n",
    "The data suggests strongly that we shouldn't advertise in the UK, but let's take a second look at India before deciding to choose Canada as our second best choice:\n",
    "\n",
    "`$59` doesn't seem like an expensive sum for people in India since they spend on average per `$66` each month.\n",
    "We have almost twice as more potential customers in India than we have in Canada:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "United States of America    74.967908\n",
       "India                       11.732991\n",
       "United Kingdom               7.163030\n",
       "Canada                       6.136072\n",
       "Name: CountryLive, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Frequency table for the 'CountryLive' column\n",
    "only_4['CountryLive'].value_counts(normalize = True) * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So it's not crystal clear what to choose between Canada and India. Although it seems more tempting to choose Canada, there are good chances that India might actually be a better choice because of the large number of potential customers.\n",
    "\n",
    "At this point, it seems that we have several options:\n",
    "\n",
    "1. Advertise in the US, India, and Canada by splitting the advertisement budget in various combinations:\n",
    "\n",
    "  * 60% for the US, 25% for India, 15% for Canada.\n",
    "  * 50% for the US, 30% for India, 20% for Canada; etc.\n",
    "2. Advertise only in the US and India, or the US and Canada. Again, it makes sense to split the advertisement budget unequally. For instance:\n",
    "\n",
    "  * 70% for the US, and 30% for India.\n",
    "  * 65% for the US, and 35% for Canada; etc.\n",
    "3. Advertise only in the US.\n",
    "\n",
    "At this point, it's probably best to send our analysis to the marketing team and let them use their domain knowledge to decide. They might want to do some extra surveys in India and Canada and then get back to us for analyzing the new survey data.\n",
    "\n",
    "# Conclusion\n",
    "In this project, we analyzed survey data from new coders to find the best two markets to advertise in. The only solid conclusion we reached is that the US would be a good market to advertise in.\n",
    "\n",
    "For the second best market, it wasn't clear-cut what to choose between India and Canada. We decided to send the results to the marketing team so they can use their domain knowledge to take the best decision."
   ]
  }
 ],
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