Finding_Bed_Markets_to_Advertise_In.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Finding the best avenues for advertising\n",
    "## It's an E-learning company that focuses in computer programming with several specializations such as web/mobile dev and data science."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib as plt\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fcc_survey = pd.read_csv('2017-fCC-New-Coders-Survey-Data.csv', low_memory = 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Initial Insights\n",
    "## Shape 18,175 Rows with 136 Columns\n",
    "## Over 75% of the survey population lives in cities with over 100,000 people. Roughly 40% more than 1,000,000.\n",
    "\n",
    "## Over 65% of the age groups are between 18 - 36, roughly 40% of the 65% is between 18-27.                            ## Roughly 40% of the population has a bachelor's degree, 17% with some college credit, or no degree, 12% with only high school diploma\n",
    "## The top five countries of Citizenship are USA, India,United Kingdom,Canada, and Brazil.\n",
    "## Approximately 80% are male\n",
    "## Over 50% are employed for wages and roughly 60% are currently working in Software Dev and IT related fields."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## This a ready-made dataset from freeCodeCamp's 2017 New Coder Survey, and was used as an alternative to a more cost intensive practice of creating a new survey\n",
    "## This survey has been framed to determine how respondents are learning to code and getting jobs\n",
    "## The data set can be downloaded from https://github.com/freeCodeCamp/2017-new-coder-survey"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Full-Stack Web Developer                                                                                                                                                                              0.117706\n",
       "  Front-End Web Developer                                                                                                                                                                             0.064359\n",
       "  Data Scientist                                                                                                                                                                                      0.021739\n",
       "Back-End Web Developer                                                                                                                                                                                0.020309\n",
       "  Mobile Developer                                                                                                                                                                                    0.016733\n",
       "Game Developer                                                                                                                                                                                        0.016304\n",
       "Information Security                                                                                                                                                                                  0.013158\n",
       "Full-Stack Web Developer,   Front-End Web Developer                                                                                                                                                   0.009153\n",
       "  Front-End Web Developer, Full-Stack Web Developer                                                                                                                                                   0.008009\n",
       "  Product Manager                                                                                                                                                                                     0.007866\n",
       "Data Engineer                                                                                                                                                                                         0.007580\n",
       "  User Experience Designer                                                                                                                                                                            0.007437\n",
       "  User Experience Designer,   Front-End Web Developer                                                                                                                                                 0.006150\n",
       "  Front-End Web Developer, Back-End Web Developer, Full-Stack Web Developer                                                                                                                           0.005578\n",
       "  DevOps / SysAdmin                                                                                                                                                                                   0.005149\n",
       "Back-End Web Developer, Full-Stack Web Developer,   Front-End Web Developer                                                                                                                           0.005149\n",
       "Back-End Web Developer,   Front-End Web Developer, Full-Stack Web Developer                                                                                                                           0.005149\n",
       "Full-Stack Web Developer,   Front-End Web Developer, Back-End Web Developer                                                                                                                           0.004434\n",
       "  Front-End Web Developer, Full-Stack Web Developer, Back-End Web Developer                                                                                                                           0.004291\n",
       "Full-Stack Web Developer,   Mobile Developer                                                                                                                                                          0.004148\n",
       "  Front-End Web Developer,   User Experience Designer                                                                                                                                                 0.004148\n",
       "Back-End Web Developer, Full-Stack Web Developer                                                                                                                                                      0.003862\n",
       "Full-Stack Web Developer, Back-End Web Developer                                                                                                                                                      0.003719\n",
       "Back-End Web Developer,   Front-End Web Developer                                                                                                                                                     0.002860\n",
       "Data Engineer,   Data Scientist                                                                                                                                                                       0.002717\n",
       "Full-Stack Web Developer, Back-End Web Developer,   Front-End Web Developer                                                                                                                           0.002717\n",
       "  Front-End Web Developer,   Mobile Developer                                                                                                                                                         0.002574\n",
       "Full-Stack Web Developer,   Data Scientist                                                                                                                                                            0.002431\n",
       "  Data Scientist, Data Engineer                                                                                                                                                                       0.002288\n",
       "  Mobile Developer, Game Developer                                                                                                                                                                    0.002288\n",
       "                                                                                                                                                                                                        ...   \n",
       "Data Engineer,   Front-End Web Developer,   Data Scientist, Back-End Web Developer,   Mobile Developer, Game Developer                                                                                0.000143\n",
       "Full-Stack Web Developer, Back-End Web Developer,   User Experience Designer,   Front-End Web Developer,   Product Manager                                                                            0.000143\n",
       "Full-Stack Web Developer, Back-End Web Developer,   Mobile Developer, Game Developer,   Front-End Web Developer                                                                                       0.000143\n",
       "  Front-End Web Developer,   Mobile Developer,   User Experience Designer, Full-Stack Web Developer, Game Developer, Back-End Web Developer                                                           0.000143\n",
       "Back-End Web Developer,   Front-End Web Developer,   Product Manager, Full-Stack Web Developer,   DevOps / SysAdmin, Data Engineer,   Mobile Developer,   Data Scientist, Information Security        0.000143\n",
       "  Data Scientist,   Front-End Web Developer,   Quality Assurance Engineer, Full-Stack Web Developer,   User Experience Designer, Back-End Web Developer, Data Engineer                                0.000143\n",
       "  Product Manager, Full-Stack Web Developer, Game Developer,   Mobile Developer                                                                                                                       0.000143\n",
       "  DevOps / SysAdmin,   Quality Assurance Engineer, Information Security, Full-Stack Web Developer, Back-End Web Developer, Game Developer,   Data Scientist,   Front-End Web Developer                0.000143\n",
       "Full-Stack Web Developer,   Product Manager,   Front-End Web Developer,   Mobile Developer,   User Experience Designer                                                                                0.000143\n",
       "  Product Manager,   Front-End Web Developer,   User Experience Designer                                                                                                                              0.000143\n",
       "  Data Scientist, Data Engineer,   Mobile Developer,   Product Manager, Back-End Web Developer                                                                                                        0.000143\n",
       "Full-Stack Web Developer, Information Security, Data Engineer,   Mobile Developer                                                                                                                     0.000143\n",
       "  Data Scientist, Data Engineer,   User Experience Designer                                                                                                                                           0.000143\n",
       "Full-Stack Web Developer,   Quality Assurance Engineer,   Product Manager, Back-End Web Developer,   Mobile Developer,   Data Scientist, Data Engineer                                                0.000143\n",
       "  Data Scientist,   Front-End Web Developer, Full-Stack Web Developer, Information Security, Back-End Web Developer                                                                                   0.000143\n",
       "  Data Scientist, Data Engineer, Back-End Web Developer, Game Developer, Information Security, Full-Stack Web Developer, AI and Machine Learning                                                      0.000143\n",
       "Full-Stack Web Developer,   Front-End Web Developer, Game Developer, Back-End Web Developer, Operating Systems, Compilers, etc...                                                                     0.000143\n",
       "Full-Stack Web Developer,   Quality Assurance Engineer                                                                                                                                                0.000143\n",
       "  DevOps / SysAdmin, Game Developer,   Product Manager, Back-End Web Developer, Information Security, Full-Stack Web Developer                                                                        0.000143\n",
       "Full-Stack Web Developer, Data Engineer,   DevOps / SysAdmin,   Data Scientist, Game Developer                                                                                                        0.000143\n",
       "Full-Stack Web Developer, Information Security, Back-End Web Developer,   Front-End Web Developer                                                                                                     0.000143\n",
       "  Front-End Web Developer, Information Security,   Quality Assurance Engineer,   Mobile Developer, Game Developer,   User Experience Designer, Back-End Web Developer                                 0.000143\n",
       "Game Developer, Full-Stack Web Developer,   Front-End Web Developer, Data Engineer,   User Experience Designer,   Data Scientist,   Mobile Developer, Back-End Web Developer, Information Security    0.000143\n",
       "Data Engineer,   Data Scientist,   Mobile Developer, Game Developer,   User Experience Designer                                                                                                       0.000143\n",
       "  Front-End Web Developer, Game Developer, Full-Stack Web Developer,   Mobile Developer, Back-End Web Developer,   User Experience Designer                                                           0.000143\n",
       "  Front-End Web Developer,   Product Manager,   User Experience Designer, Full-Stack Web Developer                                                                                                    0.000143\n",
       "Full-Stack Web Developer,   Mobile Developer, Data Engineer, Back-End Web Developer,   DevOps / SysAdmin, Game Developer                                                                              0.000143\n",
       "  DevOps / SysAdmin,   Mobile Developer, Game Developer, Full-Stack Web Developer, Back-End Web Developer,   Front-End Web Developer                                                                  0.000143\n",
       "  Mobile Developer, Back-End Web Developer, Full-Stack Web Developer, Game Developer, Data Engineer                                                                                                   0.000143\n",
       "  DevOps / SysAdmin,   Quality Assurance Engineer,   Mobile Developer, Game Developer, Back-End Web Developer                                                                                         0.000143\n",
       "Name: JobRoleInterest, Length: 3213, dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fcc_survey.head(5)\n",
    "fcc_survey['JobRoleInterest'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
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       "\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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>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>Canada</td>\n",
       "      <td>Canada</td>\n",
       "      <td>software development and IT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed for wages</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>15.0</td>\n",
       "      <td>02d9465b21e8bd09374b0066fb2d5614</td>\n",
       "      <td>eb78c1c3ac6cd9052aec557065070fbf</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>start your own business</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>English</td>\n",
       "      <td>married or domestic partnership</td>\n",
       "      <td>150.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6f1fbc6b2b</td>\n",
       "      <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",
       "      <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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>34.0</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>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",
       "      <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>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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.options.display.max_columns = 150 # to avoid truncated output \n",
    "fcc_survey.head(5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "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": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# Split each string in the 'JobRoleInterest' column\n",
    "interests_no_nulls = fcc_survey['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": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import matplotlib as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "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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vX47WrVujW7dusLW1xf3793HlyhUcOXIEXbt2ld5wixYtQnJyMjp37ozGjRuj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\nEBFCCCHEEyOBiBBCCCGemP8BhhjbERgTzlsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f47a74cb518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "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('New Coder Interest in Mobile and Web Development',y=1.08)\n",
    "plt.ylabel('% of interest')\n",
    "plt.xticks([0,1],['Web or mobile\\ndevelopment', 'Other subject'],\n",
    "           rotation = 0)\n",
    "plt.ylim(0,100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "fcc_survey_good = fcc_survey[fcc_survey['JobRoleInterest'].notnull()].copy()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "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>Brazil</th>\n",
       "      <td>129</td>\n",
       "      <td>1.886517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>125</td>\n",
       "      <td>1.828020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>112</td>\n",
       "      <td>1.637906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>102</td>\n",
       "      <td>1.491664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ukraine</th>\n",
       "      <td>89</td>\n",
       "      <td>1.301550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nigeria</th>\n",
       "      <td>84</td>\n",
       "      <td>1.228429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>77</td>\n",
       "      <td>1.126060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>75</td>\n",
       "      <td>1.096812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Romania</th>\n",
       "      <td>71</td>\n",
       "      <td>1.038315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netherlands (Holland, Europe)</th>\n",
       "      <td>65</td>\n",
       "      <td>0.950570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>62</td>\n",
       "      <td>0.906698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philippines</th>\n",
       "      <td>52</td>\n",
       "      <td>0.760456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Serbia</th>\n",
       "      <td>52</td>\n",
       "      <td>0.760456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Greece</th>\n",
       "      <td>46</td>\n",
       "      <td>0.672711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ireland</th>\n",
       "      <td>43</td>\n",
       "      <td>0.628839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>39</td>\n",
       "      <td>0.570342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>37</td>\n",
       "      <td>0.541094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>36</td>\n",
       "      <td>0.526470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Singapore</th>\n",
       "      <td>34</td>\n",
       "      <td>0.497221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>34</td>\n",
       "      <td>0.497221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Zealand</th>\n",
       "      <td>33</td>\n",
       "      <td>0.482597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Croatia</th>\n",
       "      <td>32</td>\n",
       "      <td>0.467973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>32</td>\n",
       "      <td>0.467973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norway</th>\n",
       "      <td>31</td>\n",
       "      <td>0.453349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>31</td>\n",
       "      <td>0.453349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gibraltar</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>Papua New Guinea</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aruba</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cameroon</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Guatemala</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samoa</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Qatar</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yemen</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anguilla</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rwanda</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>Somalia</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",
       "    <tr>\n",
       "      <th>Panama</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trinidad &amp; Tobago</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Liberia</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkmenistan</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vanuatu</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bolivia</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sudan</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nicaragua</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Myanmar</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Botswana</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Guadeloupe</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mozambique</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nambia</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cuba</th>\n",
       "      <td>1</td>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gambia</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",
       "Brazil                                        129    1.886517\n",
       "Germany                                       125    1.828020\n",
       "Australia                                     112    1.637906\n",
       "Russia                                        102    1.491664\n",
       "Ukraine                                        89    1.301550\n",
       "Nigeria                                        84    1.228429\n",
       "Spain                                          77    1.126060\n",
       "France                                         75    1.096812\n",
       "Romania                                        71    1.038315\n",
       "Netherlands (Holland, Europe)                  65    0.950570\n",
       "Italy                                          62    0.906698\n",
       "Philippines                                    52    0.760456\n",
       "Serbia                                         52    0.760456\n",
       "Greece                                         46    0.672711\n",
       "Ireland                                        43    0.628839\n",
       "South Africa                                   39    0.570342\n",
       "Mexico                                         37    0.541094\n",
       "Turkey                                         36    0.526470\n",
       "Singapore                                      34    0.497221\n",
       "Hungary                                        34    0.497221\n",
       "New Zealand                                    33    0.482597\n",
       "Croatia                                        32    0.467973\n",
       "Argentina                                      32    0.467973\n",
       "Norway                                         31    0.453349\n",
       "Indonesia                                      31    0.453349\n",
       "...                                           ...         ...\n",
       "Gibraltar                                       1    0.014624\n",
       "Jordan                                          1    0.014624\n",
       "Papua New Guinea                                1    0.014624\n",
       "Aruba                                           1    0.014624\n",
       "Cameroon                                        1    0.014624\n",
       "Guatemala                                       1    0.014624\n",
       "Samoa                                           1    0.014624\n",
       "Qatar                                           1    0.014624\n",
       "Yemen                                           1    0.014624\n",
       "Anguilla                                        1    0.014624\n",
       "Rwanda                                          1    0.014624\n",
       "Channel Islands                                 1    0.014624\n",
       "Somalia                                         1    0.014624\n",
       "Kyrgyzstan                                      1    0.014624\n",
       "Panama                                          1    0.014624\n",
       "Trinidad & Tobago                               1    0.014624\n",
       "Liberia                                         1    0.014624\n",
       "Turkmenistan                                    1    0.014624\n",
       "Vanuatu                                         1    0.014624\n",
       "Bolivia                                         1    0.014624\n",
       "Sudan                                           1    0.014624\n",
       "Nicaragua                                       1    0.014624\n",
       "Myanmar                                         1    0.014624\n",
       "Botswana                                        1    0.014624\n",
       "Angola                                          1    0.014624\n",
       "Guadeloupe                                      1    0.014624\n",
       "Mozambique                                      1    0.014624\n",
       "Nambia                                          1    0.014624\n",
       "Cuba                                            1    0.014624\n",
       "Gambia                                          1    0.014624\n",
       "\n",
       "[137 rows x 2 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Frequency tables with absolute and relative frequencies\n",
    "absolute_frequencies = fcc_survey_good['CountryLive'].value_counts()\n",
    "relative_frequencies = fcc_survey_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": [
    "## Top countries I would choose to advertise in would be the U.S. and the UK or Canada. Based on # of new coders, India would seem the best second choice. However I believe there will be many more social and legal challenges. UK and Canada both share a strong socioeconomic and cultural resemblence to the US."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fcc_survey_good['MonthsProgramming'] = fcc_survey_good['MonthsProgramming'].replace(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fcc_survey_good['Money_to_spend_per_month'] = fcc_survey_good['MoneyForLearning']/fcc_survey_good['MonthsProgramming']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fcc_survey_good['Money_to_spend_per_month'].isnull().value_counts(normalize=True)                                            \n",
    "#about 10% of the columns were empty values\n",
    "fcc_survey_good['Money_to_spend_per_month'] = fcc_survey_good['Money_to_spend_per_month'].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fcc_survey_good['CountryLive'] = fcc_survey_good['CountryLive'].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fcc_good = fcc_survey_good[fcc_survey_good['CountryLive'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "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_to_spend_per_month, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countries_mean = fcc_good.groupby('CountryLive').mean()\n",
    "countries_mean['Money_to_spend_per_month'][['United States of America',\n",
    "                            'India', 'United Kingdom',\n",
    "                            'Canada']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/dataquest/system/env/python3/lib/python3.4/site-packages/seaborn/categorical.py:454: FutureWarning: remove_na is deprecated and is a private function. Do not use.\n",
      "  box_data = remove_na(group_data)\n"
     ]
    },
    {
     "data": {
      "image/png": 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nTZvGwYMH8fDwYNGiRfj5+VVaU2PtxTh06AcAhRwREXEYlfXk1HvIuRE11pAj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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4761060f28>"
      ]
     },
     "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",
    "fcc_good = fcc_good[fcc_good['Money_to_spend_per_month'] < 20000]\n",
    "\n",
    "# Box plots to visualize distributions\n",
    "import seaborn as sns\n",
    "sns.boxplot(y = 'Money_to_spend_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": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "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_to_spend_per_month, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fcc_good['Money_to_spend_per_month']\n",
    "countries_mean = fcc_good.groupby('CountryLive').mean()\n",
    "countries_mean['Money_to_spend_per_month'][['United States of America',\n",
    "                            'India', 'United Kingdom',\n",
    "                            'Canada']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/dataquest/system/env/python3/lib/python3.4/site-packages/seaborn/categorical.py:454: FutureWarning: remove_na is deprecated and is a private function. Do not use.\n",
      "  box_data = remove_na(group_data)\n"
     ]
    },
    {
     "data": {
      "image/png": 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IiKhRSJs6AGo80dHhAAC5vG8TR0JERKR9bMlpJVJTryMtLQVpaSlszSEiolaB\nSU4rUdGK8/QxERGRrmKSQ0RERDqJSU4r4eExtcpjIiIiXcWBx62EXN4XtrZ9xGMiIiJdxySnFWEL\nDhERtSYSQRCEpg6isWVl5Td1CERERKQB5ub61X7GMTlERESkk5jkEBERkU5ikkNEREQ6SatJzooV\nKzBixAhMnjxZpXz//v1wc3PD5MmT8fHHH4vlISEhGD9+PNzc3HDu3Dmx/Nq1a5g8eTJcXV0RHBws\nlpeWlmLx4sUYP348Xn31Vdy5c0ebj0NEREQtiFaTHG9vb4SGhqqUXbp0CadPn8bRo0dx9OhRzJ49\nGwDw22+/ITY2FjExMdi9ezfWrFmDijHRQUFBCA4ORlxcHG7fvo2EhAQAQFhYGAwNDXHixAnMnDkT\nmzdv1ubjEBERUQui1SRn8ODBMDAwUCk7cOAA3n77bUil5bPXTUxMAADx8fFwd3eHVCqFlZUVrK2t\nkZycjKysLBQWFsLBwQEA4OnpiZMnT4rneHl5AQBcXV1x4cIFbT4OERERtSCNPibn9u3buHLlCv7x\nj3/Ax8cHV69eBQAoFAp07dpVrCeTyaBQKKBQKGBhYVGpHAD++usv8TM9PT0YGBggLy+vEZ+GiIiI\nmqtGXwxQqVTi77//xqFDh5CcnIyFCxciPj5eI9duhUv+EBERUTUaPcmxsLDA+PHjAQAODg7Q09PD\n/fv3IZPJcPfuXbHevXv3IJPJKpUrFArIZDIAQJcuXcR6SqUSBQUFMDIyUhuDsXFHSKV6Gn4yIiIi\nak60nuQ83bry0ksv4eLFixg6dChu3bqFR48ewdjYGC4uLliyZAlmzZoFhUKB9PR0ODg4QCKRQF9f\nH8nJybC3t0dUVBR8fHwAAC4uLoiMjET//v1x/PhxDB8+vFYx3b9fpPHnJCIiosZX04rHWt3WwdfX\nF5cuXUJeXh7MzMywYMECeHh4wN/fH6mpqWjbti38/PwwdOhQAOVTyMPCwiCVShEQEIBRo0YBAK5e\nvQp/f3+UlJTA2dkZK1euBFA+hXzp0qVISUmBkZERtmzZAisrK7VxcVsHIiIi3dBkSU5zxSSHiIhI\nN3DvKiIiImp1mOQQERGRTmKSQ0RERDqJSQ4RERHpJCY5REREpJOY5BAREZFOYpJDREREOolJDhER\nEekkJjlERESkk5jkEBERkU5iktOKnDgRgxMnYpo6DCIiokah9V3IqfmIjo4AAIwf797EkRAREWkf\nW3JaiRP64IP8AAAgAElEQVQnYlBcXITi4iK25hARUavAJKeVqGjFefqYiIhIVzHJISIiIp3EJKeV\n8PDwrvKYiIhIVzHJaSXGj3fHM890xDPPdOTAYyIiahU4u6oVYQsOERG1JhJBEISmDqKxZWXlN3UI\nREREpAHm5vrVfsbuKiIiItJJTHKIiIhIJzHJISIiIp3EJIeIiIh0EpMcIiIi0klMcoiIiEgnMckh\nIiIincQkh4iIiHQSkxwiIiLSSVpNclasWIERI0Zg8uTJlT7bu3cv5HI58vLyxLKQkBCMHz8ebm5u\nOHfunFh+7do1TJ48Ga6urggODhbLS0tLsXjxYowfPx6vvvoq7ty5o83HafFSU68jNfV6U4dBRETU\nKLSa5Hh7eyM0NLRS+b179/C///0P3bp1E8t+++03xMbGIiYmBrt378aaNWtQseNEUFAQgoODERcX\nh9u3byMhIQEAEBYWBkNDQ5w4cQIzZ87E5s2btfk4LV50dDiio8ObOgwiIqJGodUkZ/DgwTAwMKhU\nvn79eixbtkylLD4+Hu7u7pBKpbCysoK1tTWSk5ORlZWFwsJCODg4AAA8PT1x8uRJ8RwvLy8AgKur\nKy5cuKDNx2nRUlOvIy0tBWlpKWzNISKiVqHRx+TEx8eja9eusLW1VSlXKBTo2rWr+LVMJoNCoYBC\noYCFhUWlcgD466+/xM/09PRgYGCg0v1F/+fJFhy25hARUWsgbcybPXz4ECEhIdi7d69Wrl/bDdWN\njTtCKtXTSgzNVdu2eirHNe3aSkREpAsaNclJT09HZmYmPDw8IAgCFAoFvL29cfjwYchkMty9e1es\ne+/ePchkskrlCoUCMpkMANClSxexnlKpREFBAYyMjNTGcf9+keYfrplzd/fE1atXxeOsrPwmjoiI\niKjhavqjXevdVU+2rvTu3Rv/+9//EB8fj1OnTkEmkyEyMhKmpqZwcXFBTEwMSktLkZGRgfT0dDg4\nOMDc3Bz6+vpITk6GIAiIiorC2LFjAQAuLi6IjIwEABw/fhzDhw/X9uO0WHJ5X9ja9oGtbR/I5X2b\nOhwiIiKt02pLjq+vLy5duoS8vDyMGTMGCxYswNSpU8XPJRKJmATZ2NjAzc0NEydOhFQqRWBgICQS\nCQBg9erV8Pf3R0lJCZydneHs7AwAeOWVV7B06VKMHz8eRkZG2LJlizYfp8Xz8JiqvhIREZGOkAi1\nHciiQ9hVQ0REpBuatLuKiIiIqCkwySEiIiKdxCSHiIiIdBKTHCIiItJJTHKIiIhIJzHJISIiIp1U\n4zo5CoUCUVFRuHDhAjIyMiAIAqysrODk5AQvLy+VPaWIiIiImpNq18lZs2YNkpKSMG7cOAwYMEBM\naBQKBZKSkvD9999j4MCBCAwMbNSANYHr5BAREemGmtbJqTbJOXPmDMaMGVPjhWtTpzlikkNERKQb\n6pXk6DImOURERLqhQSseb9y4Efn5+SgrK8P06dPh6OiI6OhojQZIREREpGlqk5zz589DX18f586d\ng0wmQ1xcHPbu3dsYsRERERHVW62nkF++fBnjxo2DTCYTdwcnIiIiaq7UJjmmpqYIDAxEbGwsRo4c\nibKyMiiVysaIjYiIiKje1A48zs3NxZEjR+Do6AhHR0f8+eefSExMhLe3d2PFqHEceExERKQb6j27\nSqlUYt68eQgJCdFKYE2FSQ4REZFuqPfsKj09PeTl5aEVzjInIiKiFq7GbR0AoH///pg/fz4mTZqE\nTp06ieWjR4/WamBEREREDaE2yUlJSQEAHDhwQCyTSCRMcoiIiKhZ44rHrUhq6nUAgFzet4kjISIi\n0oyaxuSobckBgPz8fNy6dQslJSVi2ZAhQxoeGTWq6OhwAExyiIiodVCb5MTExGDTpk148OABunTp\ngvT0dMjlckRGRjZGfKQhqanXkZaWIh4z0SEiIl2ndjHAnTt3IiIiAtbW1oiLi8OePXtgb2/fGLGR\nBlW04jx9TEREpKvUJjlSqRSmpqbiKscjR47EL7/8ovXAiIiIiBpCbZLTrl07CIIAa2tr7N+/H6dO\nnUJRUVFjxEYa5OExtcpjIiIiXaV2TM7ChQtRUFCAJUuWICgoCPn5+QgMDGyM2EiD5PK+sLXtIx4T\nERHpOk4hb0U4hZyIiHRNvfau+vbbb2u86IwZM9TeeMWKFThz5gxMTU1x9OhRAMBHH32E06dPo127\ndnj22WexYcMGdO7cGQAQEhKC8PBw6OnpISAgAKNGjQIAXLt2DX5+figtLYWzszMCAgIAAKWlpVi+\nfDmuXbsGY2NjbN26Fd26dVMbV2tNcoiIiHRNvfauunr1ao3/asPb2xuhoaEqZaNGjcKxY8cQHR0N\na2trcfPPmzdvIjY2FjExMdi9ezfWrFkj7pkVFBSE4OBgxMXF4fbt20hISAAAhIWFwdDQECdOnMDM\nmTOxefPmWsVFREREuq/aMTkbNmxo8MUHDx6MzMxMlbIRI0aIx46OjoiLiwMAnDp1Cu7u7pBKpbCy\nsoK1tTWSk5PRrVs3FBYWwsHBAQDg6emJkydP4oUXXkB8fDzef/99AICrqys+/PDDBsdMREREuqHa\nJOfs2bM1nqiJvavCwsIwadIkAIBCoYCjo6P4mUwmg0KhgJ6eHiwsLCqVA8Bff/0lfqanpwcDAwPk\n5eXByMiowbERERFRy1ZtkrNnz55qT9LEBp3/+te/0LZtWzHJ0YRWOIaaiIiIqlFtkrN//36t3TQi\nIgJnz57Fvn37xDKZTIa7d++KX9+7dw8ymaxSuUKhgEwmAwB06dJFrKdUKlFQUFCrVhxj446QSvU0\n+ERERETU3NRqg86EhAScP38eQPnA4ZEjR9b6Bk+3rvz3v/9FaGgovvnmG7Rr104sd3FxwZIlSzBr\n1iwoFAqkp6fDwcEBEokE+vr6SE5Ohr29PaKiouDj4yOeExkZif79++P48eMYPnx4rWK6f5+LGRIR\nEemCek0hr7Bnzx5ERUVh4sSJAMo37PT09MScOXPU3tjX1xeXLl1CXl4ezMzMsGDBAoSEhODRo0di\ni0v//v0RFBQEoHwKeVhYGKRSqcoU8qtXr8Lf3x8lJSVwdnbGypUrAZRPIV+6dClSUlJgZGSELVu2\nwMrKSm1cnEJORESkGxqU5EyePBkHDhwQ17IpKCjAtGnTxHVvWiImOURERLqhXuvkPKkiwXn6mIiI\niKi5Ujsmx87ODv7+/njllVcAlE/7trOz03pgRERERA2htruqqKgIO3bswIULFwCUL+Y3b948dOzY\nsVEC1AZ2VxEREemGBo3J0UVMcoiIiHRDTUlOtd1VH330UY0XXbZsWf0jIiIiItKyagced+zYER07\ndkR2djZiY2NRVlaGsrIyHD9+HDk5OY0ZIxEREVGdqe2ueuONN/Dpp5/C2NgYAHD//n0sXLhQZbXi\nlobdVURERLqhQVPIs7OzxQQHAIyNjZGdna2ZyIiIiIi0RO0UchsbGwQEBODll18GUL7vlI2NjdYD\nIyIiImoItd1VBQUF2LFjBy5dugQAGDZsGObPn9+iFwVkdxUREZFu4BTypzDJISIi0g0N3taBiIiI\nqKVhkkNEREQ6iUlOK5Kaeh2pqdebOgwiIqJGoXZ2VYUHDx4gMTERVlZWkMvl2oyJtCQ6OhwAIJf3\nbeJIiIiItK/alpwlS5YgNTUVAJCXl4fJkydj69atmD17Ng4fPtxoAZJmpKZeR1paCtLSUtiaQ0RE\nrUK1Sc7169fFFpvo6Gg8//zzOHbsGCIiIvDNN980WoCkGRWtOE8fExER6apqk5z27duLxz/88ANe\neuklAICFhQUkEon2IyMiIiJqgBoHHisUCjx8+BCJiYkYOnSoWF5SUqL1wEizPDymVnlMRESkq6od\neDx37lx4enqibdu2GDRokLiVw08//YRu3bo1WoCkGXJ5X9ja9hGPiYiIdF2NKx5nZWUhOzsbcrlc\n7KJSKBRQKpUtOtFprSseVww4ZpJDRES6gts6PKW1JjlERES6pqYkp9ruqidbbyqYmppi5MiRWLFi\nBQwNDTUXIREREZGGVduSU1RUVKksNzcXBw8ehEKhwObNm7UenLawJYeIiEg3aLy7ytPTE1FRUQ0K\nqikxySEiItINGt+FnOvkEBERUXNX672rAEAQBISFhUEmk2krHiIiIiKNqDbJGT58eKUWm/z8fDg4\nOLTo8ThERETUOlQ7JiczM1O1okQCY2NjPPPMM7W++IoVK3DmzBmYmpri6NGjAIC///4bixcvRmZm\nJqysrLBt2zbo65f3p4WEhCA8PBx6enoICAjAqFGjAADXrl2Dn58fSktL4ezsjICAAABAaWkpli9f\njmvXrsHY2Bhbt26t1fo9HJNDRLqK62FRa1OvMTmWlpYq/7p161anBAcAvL29ERoaqlK2a9cuODk5\nIS4uDsOGDUNISAgA4ObNm4iNjUVMTAx2796NNWvWoCL/CgoKQnBwMOLi4nD79m0kJCQAAMLCwmBo\naIgTJ05g5syZbGEiolYvOjqcm/AS/X/VJjnvvPMOLl++XO2JiYmJePfdd2u8+ODBg2FgYKBSFh8f\nDy8vLwCAl5cXTp48CQA4deoU3N3dIZVKYWVlBWtrayQnJyMrKwuFhYVwcHAAUD6zq+KcJ6/l6uqK\nCxcuqHteIiKdlZp6HWlpKUhLSxFbdIhas2rH5Pj6+uKzzz7DsmXLYGdnJw42VigUuHbtGvr06YPF\nixfX+Ya5ubkwMzMDAJibmyM3N1e8rqOjo1hPJpNBoVBAT08PFhYWlcoB4K+//hI/09PTg4GBAfLy\n8mBkZFTnuIiIWronW3Cio8PZZUWtXrVJTu/evfHZZ58hNzcXiYmJ+PPPPwEAgwYNQmBgoJioNJQm\np6PXdskfY+OOkEr1NHZfIqLmoG1bPZXjmsYqELUGaqeQm5iYYMKECRq7oampKbKzs2FmZoasrCyY\nmJgAKG+huXv3rljv3r17kMlklcoVCoXYqtSlSxexnlKpREFBQa1ace7fr7yaMxFRS+fu7omrV6+K\nx5xkQa2BxhcDrIunW1dcXFwQEREBAIiMjMTYsWPF8piYGJSWliIjIwPp6elwcHCAubk59PX1kZyc\nDEEQEBUVpXJOZGQkAOD48eMYPny4th+HiKjZksv7wta2D2xt+7Crigha3oXc19cXly5dQl5eHszM\nzLBgwQK89NJLWLhwIe7evQtLS0ts27ZNHJwcEhKCsLAwSKVSlSnkV69ehb+/P0pKSuDs7IyVK1cC\nKJ9CvnTpUqSkpMDIyAhbtmyBlZWV2rj41w0R6SpOIafWRuN7V7V0THKIiIh0Q01JTq23dSgtLYVS\nqRS/ruuaOURERESNSW2S8/3332Pt2rXIysoCUD7GRiKRICUlRevBEREREdWX2u6qcePGYdOmTXB0\ndESbNlofp9wo2F1FRESkGxrUXWVoaIiBAwdqNCAiIiIibau2aaa4uBjFxcUYN24c/v3vfyMvL08s\nKy4ubswYiYiIiOqs2u4quVwOiUSiss5NxdctfUwOu6uIiIh0A6eQP4VJDhERkW5o0IrHwcHBtSoj\nIiIiak7UJjlXrlypVHb58mWtBENERESkKdXOroqNjUVsbCwyMzOxcOFCsbygoAAdOnRolOBIs7jc\nOxERtSbVJjk9evTAmDFj8Msvv2DMmDFieefOneHk5NQYsZGGRUeHA2CSQ0RErUO1SY5cLodcLoeL\niwuMjIwaMybSgtTU60hLSxGPmegQEZGuU7sYoFKpxLZt25CRkYGysjKx/NNPP9VqYKRZFa04FcdM\ncoiISNepTXIWLFiA559/Hk5OTtDT02uMmIiIiIgaTG2S8+DBA6xdu7YxYiEt8vCYio8+WiceExER\n6Tq1SU6vXr2gUCggk8kaIx7SErm8L2xt+4jHREREuq5WLTlTpkzBgAED0L59e7GcY3JaHrbgEBFR\na6I2yZk0aRImTZrUGLGQlrEFh4iIWhPuXUVEREQtVoP2rsrNzcXixYsxfPhwDB8+HL6+vsjNzdVo\ngERERESapjbJCQwMxHPPPYfo6GhERUXB2toaq1evbozYiIiIiOpNbZKTnp6OhQsXQiaTwcLCAu+/\n/z4yMjIaIzYiIiKielOb5Dx+/Bg5OTni1zk5OXj8+LFWgyIiIiJqKLWzq+bMmQNPT09xk86zZ8/C\n19dX23ERERERNUitZlf9+uuvSExMBAAMGzYMvXr10npg2sTZVURERLqhptlVnEJORERELVZNSY7a\n7qorV65gy5YtSE9Ph1KphCAIkEgkuHDhgkaDJCIiItIktUlOQEAAFi1aBDs7O7Rpo3accq2FhITg\nyJEjaNOmDXr37o0NGzaguLgYixcvRmZmJqysrLBt2zbo6+uL9cPDw6Gnp4eAgACMGjUKAHDt2jX4\n+fmhtLQUzs7OCAgI0FiMRERE1HKpzVr09fXh5uaG7t27w9LSUvzXEJmZmTh06BAiIyNx9OhRKJVK\nHDt2DLt27YKTkxPi4uIwbNgwhISEAABu3ryJ2NhYxMTEYPfu3VizZg0qetmCgoIQHByMuLg43L59\nGwkJCQ2KTZedOBGDEydimjoMIiKiRqE2yZk4cSIOHDiAvLw8FBcXi/8aonPnzmjbti2Ki4tRVlaG\nhw8fQiaTIT4+Hl5eXgAALy8vnDx5EgBw6tQpuLu7QyqVwsrKCtbW1khOTkZWVhYKCwvh4OAAAPD0\n9BTPocqioyMQHR3R1GEQERE1CrVJjqmpKTZt2gQnJycMHDgQAwYMwMCBAxt0U0NDQ8yePRtjxoyB\ns7Mz9PX1MWLECOTk5MDMzAwAYG5uLm4foVAo0LVrV/F8mUwGhUIBhUIBCwuLSuVU2YkTMSguLkJx\ncRFbc4iIqFVQm+Rs3boV+/fvx7Vr15CSkoLU1FSkpKQ06KYZGRn46quvcPr0aSQkJKC4uBhHjhyB\nRCJRqff011R/T7bgsDWHiIhaA7UDj2UyGezt7TV6019++QUDBw6EkZERAOCll17Cjz/+CFNTU2Rn\nZ8PMzAxZWVkwMTERY7h79654/r179yCTySqVKxQKyGQytfc3Nu4IqVRPo8/U3D2ZL0okNU+5IyIi\n0gVqk5zhw4dj8+bNcHd3R/v27cVyGxubet+0Z8+e+Ne//oWSkhK0a9cOFy9ehL29PTp27IiIiAjM\nnTsXkZGRGDt2LADAxcUFS5YswaxZs6BQKJCeng4HBwdIJBLo6+sjOTkZ9vb2iIqKgo+Pj9r7379f\nVO/YW6opU7xx8OA34jHXCiIiIl3QoMUAXVxcKp8kkSA+Pr5BQe3ZsweRkZFo06YN+vbti3Xr1qGw\nsBCLFi3C3bt3YWlpiW3btsHAwABA+RTysLAwSKVSlSnkV69ehb+/P0pKSuDs7IyVK1eqvXdr/QU/\nf/5bAIAdO/Y0cSRERESawRWPn9Jak5yKAcfjx7s3cSRERESawSTnKa01ySEiItI1NSU5mlvCmIiI\niKgZYZJDREREOqnGJEepVGL79u2NFQsRERGRxtSY5Ojp6eG///1vY8VCREREpDFqu6vGjBmD0NBQ\n5OTkaGzvKiIiIiJtUzu7Si6X/19liQSCIEAikTR4a4emxNlVREREuoFTyJ/CJIeIiEg3NHgK+a1b\nt3Dy5EkAQGFhIfLy8jQTGREREZGWqE1yIiIi8N5772HDhg0AyjfBXLRokdYDIyIiImoItUnOvn37\nEB4eDn398uagnj17Ijs7W+uBERERETWE2iSnbdu26NSpk0qZnp6e1gIiIiIi0gS1SY6RkRFu3boF\niUQCAIiOjoaFhYXWAyMiIiJqCLWzq27dugVfX1/8/vvvMDExQYcOHbBz5048++yzjRWjxnF2FRER\nkW5o8BRypVKJ27dvQxAE9OjRo8V3VzHJISIi0g01JTnS2lzgt99+Q2Jiovi1jY1Nw6MiIiIi0iK1\nY3K+/fZbzJkzB2lpaUhLS8Ps2bPx73//uzFiIw1LTb2O1NTrTR0GERFRo1DbkrNv3z5ERUXB1NQU\nAJCbm4tp06Zh+vTpWg+ONCs6OhwAIJf3beJIiIiItE9tS06nTp3EBAcATExMKk0pp+YvNfU60tJS\nkJaWwtYcIiJqFdS25IwcORIBAQF4+eWXAQCRkZF44YUXcPPmTQAcn9NSVLTiVByzNYeIiHSd2iTn\n2LFjAIALFy6olB89ehQSiQTx8fHaiYyIiIioAdQmOadOnWqMOEjLBgwYhLS0FPGYiIhI19VqF3Jq\n+X788Ycqj4mIiHQVkxwiIiLSSUxyWgkPj6lVHhMREekqtWNy7t27xw05dYBc3he2tn3EYyIiIl2n\nNsl5+eWXMWDAAEyfPh1OTk6NERNpCVtwiIioNVG7QWdpaSliYmJw4MAB5OfnY8aMGfDw8EDnzp0b\nK0aN4wadREREuqHBu5BXSEpKwgcffIAHDx7Ay8sL8+bNU1kNuS7y8/MREBCAGzduoE2bNli/fj2e\ne+45LF68GJmZmbCyssK2bdugr18efEhICMLDw6Gnp4eAgACMGjUKAHDt2jX4+fmhtLQUzs7OCAgI\nUHtvJjlERES6oaYkp1YDjzMzM/HJJ5/A19cXTk5O2LNnD0xNTTFnzpx6BxUcHIzRo0cjNjYW0dHR\n6NmzJ3bt2gUnJyfExcVh2LBhCAkJAQDcvHkTsbGxiImJwe7du7FmzRpU5GZBQUEIDg5GXFwcbt++\njYSEhHrHRERERLpDbZLzzjvvwMfHB/r6+oiIiMCGDRswcOBAzJs3D2VlZfW6aUFBAa5cuYKpU8vH\niEilUujr6yM+Ph5eXl4AAC8vL5w8eRJA+YKE7u7ukEqlsLKygrW1NZKTk5GVlYXCwkI4ODgAADw9\nPcVziIiIqHVTO/DYy8sL48aNg56eXqXPvvvuu3rd9M8//4SxsTH8/f2RmpoKOzs7rFixAjk5OTAz\nMwMAmJubIzc3FwCgUCjg6Ogoni+TyaBQKKCnp6cy86uinIiIiEhtkjNhwgRcuHABv/32G15//XVk\nZ2cjPz8fPXr0qPdNy8rKcP36daxevRr29vZYv349du3aBYlEolLv6a81xdi4I6TSykkbERER6Q61\nSc6uXbtw9uxZZGVl4fXXX0dZWRlWrFiBAwcO1PumFhYWsLCwgL29PQBg/Pjx2L17N0xNTZGdnQ0z\nMzNkZWXBxMQEQHkLzd27d8Xz7927B5lMVqlcoVBAJpOpvf/9+0X1jp2IiIiajwYNPP7uu+/w1Vdf\noWPHjgDKE5SCgoIGBWRmZoauXbvi1q1bAICLFy/CxsYGLi4uiIiIAABERkZi7NixAAAXFxfExMSg\ntLQUGRkZSE9Ph4ODA8zNzaGvr4/k5GQIgoCoqCjxHKosNfU6UlOvN3UYREREjUJtS06HDh3Qtm1b\nlTJNdCOtXLkSS5YsQVlZGbp3744NGzZAqVRi0aJFCA8Ph6WlJbZt2wYAsLGxgZubGyZOnAipVIrA\nwEAxhtWrV8Pf3x8lJSVwdnaGs7Nzg2PTVdHR4QC44jEREbUOapMcCwsLXLlyBRKJBI8fP8bOnTvR\nq1evBt9YLpcjPDy8UvlXX31VZf133nkH77zzTqVyOzs7HD16tMHx6LrU1OtIS0sRj5noEBGRrlPb\nXbVq1Sp88cUXuHHjBvr374/Lly9jxYoVjREbaVBFK87Tx0RERLpKbUuOubk59u7di+LiYjx+/Bid\nOnVqjLiIiIiIGkRtkgMA6enpSE9Ph1KpFMtGjx6ttaBI8zw8puKjj9aJx0RERLpObZLzySef4PDh\nw3j++efRpk1575ZEImGS08LI5X3Rvfuz4jEREZGuU5vkHD9+HCdPnmzRu44TERFR66N24LG5uTkT\nHB2QmnodGRnpyMhI51o5RETUKqhtyXF0dMQHH3yACRMmoH379mI5u6talqdnV7HLioiIdJ3aJOeX\nX34BAOzfv18s45gcIiIiau4kgiAITR1EY8vKym/qEBpdaup1cXbVsmUr2ZJDREQ6oaa9q2o1hTwh\nIQHnz58HAIwaNQojR47UTGTUaOTyvrC17SMeExER6Tq1A4/37NmDTZs2wcDAAAYGBti4cSNCQ0Mb\nIzbSsPz8B8jPf9DUYRCRFu3fvxf79+9t6jCokXED5qqpbcmJjo7GwYMHxRlWPj4+mDZtGubMmaP1\n4Eiz7tzJbOoQiEjLzp49BQDw8ZndxJFQY+IGzFVT25IDQGUKOaeTt0zBwYFVHhOR7ti/fy8eP36M\nx48fszWnFanYgDktLYWtOU9Rm+TY2dnB398fSUlJSEpKwooVK2BnZ9cYsZEG/fbbjSqPiUh3VLTi\nPH1Muo0bMFdPbXfVqlWrsGPHDqxbVz4zZ8SIEZg3b57WAyMiIiJqCLVJTseOHbF06dLGiIW06Pnn\ne4ktOM8/36uJoyEibRg92gWnT58Uj6l14AbM1at2nZxvv/22xhNnzJihlYAaQ2tcJwcAZs+eDgDY\nu/ffTRwJEWnLW2+9DgDYs+ebJo6EGtOmTWsBAMuXr2riSBpfvdbJWbt2Lfr164fevXtrJShqfB06\ndGjqEIhIy9iC0zqxBadq1SY569evR2RkJG7cuAEvLy9MmjQJhoaGjRkbaVBq6nU8fPhQPOY0QyLd\nxKnjrRP/n161amdXeXt7Y//+/di6dStyc3Px2muvYeHChUhNTW3M+EhDOPqeiIhaG7VTyLt3745Z\ns2bhjTfeQGJiorhhJ7UsRUWFVR4TERHpqmq7qwRBQEJCAiIiInDjxg24ubnh0KFD6N69e2PGRxpS\n0VX19DEREZGuqjbJcXZ2RpcuXeDt7Y358+dDIpGgpKQEN2/eBADY2Ng0WpDUcAUFBVUeExER6apq\nk5y2bdvi/v37CA0Nxd69e/HkTHOJRIL4+PhGCZA0w8zMDBkZ6eIxERGRrqt2nRxd1hrXyUlNvS4u\nFrVs2UqOxCciIp1Q0zo5tdqgk4iIWobU1OvcpJHo/2OS00pwCjlR6xAdHc7/xon+vyZNch4/fgwv\nL2b283AAABRiSURBVC+8++67AIC///4bs2fPhqurK+bMmYP8/P/rVgoJCcH48ePh5uaGc+fOieXX\nrl3D5MmT4erqiuDg4EZ/BiKi5iI19TrS0lKQlpbC1hwiNHGSs2/fPjz//PPi17t27YKTkxPi4uIw\nbNgwhISEAABu3ryJ2NhYxMTEYPfu3VizZo04EDooKAjBwcGIi4vD7du3kZCQ0CTP0tw9ueQ3l/8m\n0k1ssSVS1WRJzr1793D27Fm88sorYll8fDy8vLwAAF5eXjh5snw33VOnTsHd3R1SqRRWVlawtrZG\ncnIysrKyUFhYCAcHBwCAp6eneA6penKgMQcdExFRa9BkSc769euxbNkySCQSsSwnJ0ec3mxubo7c\n3FwAgEKhQNeuXcV6MpkMCoUCCoUCFhYWlcqpsu3bP67ymIh0B1tsiVQ1SZJz5swZmJmZoU+fPqhp\nBvuTCRA1zE8/JVV5TES6Qy7vC1vbPrC17cMWWyLUsBigNiUlJeHUqVM4e/YsSkpKUFhYiKVLl8LM\nzAzZ2dkwMzNDVlYWTExMAJS30Ny9e1c8/969e5DJZJXKFQoFZDKZ2vsbG3eEVKqn+QdrQWpaV4CI\nWq6ZM30A8L9xIqCJkpwPPvgAH3zwAQAgMTERe/fuxebNm/HRRx8hIiICc+fORWRkJMaOHQsAcHFx\nwZIlSzBr1iwoFAqkp6fDwcEBEokE+vr6SE5Ohr29PaKiouDj46P2/vfvF2n1+ZojR8eBYguOo+PA\nVrkgIlFrYGHxHIDWuegptU4tZjHAuXPn4vz583B1dcXFixcxd+5cAOX7ZLm5uWHixImYO3cuAgMD\nxa6s1atXIyAgAK6urrC2toazs3NTPkKz9f77S6o8JiIi0lXc1qEVqRhwzCSHiIh0RU0tOUxyiIiI\nqMVqMd1VpF3c04bo/7V370FR1f0fwN+7i66AFiCIhkCj/pTUsRKfMWcca1ARZRZYFOQxL6moeSNr\nfMZwUnPMiseki6ipY1r99AkvsFzERyasTJOfmXlBWEYtFVG5mAoCCcvu7w/GI8ghL7Ec9nver78+\ne9hzznc9rLzP9/s95xCRmigy8ZiUce8OqLy0lIiI1IA9OSrBZ9oQEZHaMOSoBJ9pQ6QOHJYmuo/D\nVUREAuGwNNF97MlRCWdnZ9maiMTBYWmiphhyVILPriISH4eliZpiyCEiIiIhMeQQEQkiPHy8bE2k\nVpx4rBJPP+2G27dvSTURiScgoD/69XtOqonUjiFHJbp37yGFnO7deyjcGiKyF/bgEN3HkKMSFotF\ntiYisbAHh+g+zslRiQsXzsnWREREomLIISIiIiEx5KhE797/I1sTERGJiiFHJZycnGRrIiIiUTHk\nqER1dZVsTUREJCqGHJWoqKiQrYmIiETFkKMSlZUVsjUREZGoGHJUokOHDrI1ERGRqBhyVEKv18vW\nREREomLIUQnOySEiEpfZnA+zOV/pZrQ7vJaYiIjIwaWl7QXAx3o8iD05REREDsxszkdhYQEKCwvY\nm/MAhhwiIiIHdq8X58GaGHKIiIhIUAw5KqHRaGRrIiJybOHh42VrUijkXL9+HVOnTkVoaCgMBgO+\n+uorAMDt27cxY8YMjBkzBjNnzkRlZaW0zqZNmxAcHIyxY8fi8OHD0vKzZ8/CYDBgzJgxWL16dZt/\nFkdhs9lkayISS3Z2FrKzs5RuBrWhgID+8PX1g6+vHyceP0CRkKPT6RAfH499+/bhm2++wY4dO3Dh\nwgVs3rwZw4YNw4EDBzB06FBs2rQJAHD+/Hns378fWVlZ2LJlC1auXCn9oX733XexevVqHDhwABcv\nXsSPP/6oxEdq93gzQCJ1SEtLQVpaitLNIGoXFAk5Xl5eeO655wAArq6u6N27N0pKSpCTkwOj0QgA\nMBqN+PbbbwEABw8exLhx4+Dk5ISePXvC398fp0+fRllZGaqqqjBo0CAAQEREhLQONVVfXy9bE5E4\nsrOzUFNTjZqaavbmqIjZnI+iossoKrrMq6seoPicnCtXrsBsNuP555/HjRs34OnpCaAhCP3xxx8A\ngJKSEvTo0UNax9vbGyUlJSgpKUH37t2bLafmrFarbE1E4mjcg8PeHPXg1VUtU/RmgFVVVYiLi8PS\npUvh6urabEKsvSbIuru7wMlJZ5dtOwovry5KN4GIWlnj/zI1Gn7P1aJDB12Tmsf9PsVCjsViQVxc\nHMLDwzFq1CgAQNeuXVFeXg5PT0+UlZXBw8MDQEMPzbVr16R1r1+/Dm9v72bLS0pK4O3t/dB937xZ\n3cqfpv3TarVSD45Wq0VZWeVD1iAiRxMWFolvvvlfqeb3XB3GjYtAXl6eVKvtuP9VqFNsuGrp0qXo\n06cPpk2bJi0LCgpCSkpDF2tqaipGjhwpLc/KykJtbS2Kiopw+fJlDBo0CF5eXujSpQtOnz4Nm80G\nk8kkrUNN6fWdZGsiEkdw8Djo9Xro9XoEB49TujnURgIC+sPZ2QXOzi68uuoBivTk/PLLL8jIyEDf\nvn0REREBjUaDN998E7NmzcKiRYuwd+9e+Pj44JNPPgEA9OnTB2PHjkVoaCicnJywYsUKaShr+fLl\niI+Px927dzFixAiMGDFCiY/U7lksdbI1EYnlqaeeVroJ1MbM5nzU1FRLNYPOfYqEnMDAQBQUFMj+\nbPv27bLL58yZgzlz5jRbPnDgQGRkZLRm84RUV1cnWxOROMzmfJSVlUo1/9ipw4MTj3nc71P86ioi\nImodvMqGqCmGHCIiIgfGxzq0jCGHSGBmcz5vDqYiL74YKFsTqRVDDpHA0tL2cthCRX799RfZmsTG\nYcqWMeQQCcpszkdhYQEKCwvYm0NEqsSQQyQont2pD+dmqNMzz/jI1sSQQ0QkDN4UTp1yc3+SrYkh\nh0hYnISqPvduCldTU80hSiIw5BAJ68iRQ7I1iYtDlOoUHh4pWxNDDpGwysvLZWsiEktw8DhotVpo\ntVo+s+wBDDlEgvL09JStSVyceKxOZnM+rFYrrFYrhykfwJBDJKh//nOqbE3iajzZmBOP1YPDlC1j\nyCEiEsSiRa/L1kRqxZBDJKj//Ocr2ZrEVVFRIVuT2HglZcsYcogExYnHROqQk5MtWxNDDpGwOPFY\nfbRarWxNYrtxo1y2JoYcImFx4rH6+Pj0lK1JbDqdTrYmwEnpBhCRfQQE9Ievr59UE5GY3NzcUVZW\nKtV0H0MOkcDYg0MkPg+PrlLI8fDoqnBr2heGHCKBsQeHSHzPPOODwsICqab7OCeHiEgQLi6usjWJ\njU8hbxlDDpHAzOZ83uZdRRqfxfOMXj2s1nrZmhhyiIS2bdtmbNu2WelmUBv54YfvZGsSW6dOzrI1\nMeQQCctszkdZWSnKykrZm6MSPKNXpz//rJGtiSGHSFiNe3DYm0Mkrrq6OtmaGHKIhFVeXiZbE5FY\nrFarbE0MOUTCstlssjURkVoIEXIOHTqEkJAQjBkzBps3s1ueiIiIBAg5VqsVq1atwtatW5GZmYl9\n+/bhwoULSjeLiIiIFObwdzw+ffo0/P394ePTcE+I0NBQ5OTkoHfv3gq37PHs2rUDP//8f222v3/9\nK85u2/7HP4YiOvpVu22fiIjoUTh8yCkpKUGPHj2k197e3jhz5kyr7uP999/FzZt/tOo2H1RVVYXa\n2rt23Udj9vw8339/0O6Bzd3dA0uXvmu37Yt4zGNjJ9tt2x076uHqat877Nr7mLcFnsy0LyJ+zwF+\n1xtz+JDTFq5cKRLu3gP2nIH/5581dv/3qqqqsuv2ecwfjwjHfNeuHcjO3m/XfbT1lS83bpTbbdv/\n/e8+u/97BQePtWuQEvF7DvC73pjG5uCXXZw8eRLr1q3D1q1bAUCaeDx79mwlm9UuGQwGAEBGRobC\nLaG2EBERgfr6hhvC6XQ6mEwmhVtE9nbvO34Pv+vqsHHjRmRlZQEAxo0bh7lz5yrcovbD4UNOfX09\nQkJCsH37dnh5eSEqKgqJiYkONyeHiIiIWpfDD1fpdDosW7YMM2bMgM1mw4QJExhwiIiIyPF7coiI\niIjkOPx9coiIiIjkMOQQERGRkBhyiIiISEgMOYIqLi5udjlpUlIStm3bhlOnTiE6OhoREREIDQ1F\nUlKSQq2k1tTSMf/iiy8QHx+P7OxsAMCtW7dgNBqRmpqqRDPpCb344ouP9f5jx47h9ddfBwAcPHgQ\nW7ZssUezqBWUl5fjrbfeQnBwMMaPH485c+bg0qVLdtvf4/4uOTKHv7qKHo/NZsOSJUvw2WefoW/f\nvrDZbPjtt9+Ubha1kTt37iA2NhYxMTEwGo1KN4ceg0ajeeJ1g4KCEBQU1Iqtoda0YMECREZGIjEx\nEQBQWFiI8vJy+Pv722V/f+d3ydEw5KjQzZs34enpCaDhl52X3KtDVVUVYmNjERYWhokTJyrdHHpC\nx44dw7p16+Du7o5z585h4MCBWLNmDQDg0KFD+OCDD+Ds7IzBgwdL66SmpiIvLw/Lli3Dd999h40b\nN8JiscDNzQ0fffQRPDw8lPo4qpebm4sOHTogOjpaWtavXz9UV1fjtddeQ0VFBSwWC9544w2MHDkS\nxcXFmDVrFgIDA/Hrr7/C29sbGzduRMeOHbF7924kJyfDYrHAz88Pa9asgV6vx5UrV7B48WJUV1c3\nCbvV1dWYN29es32IhMNVKqPRaDBt2jSEhIRg4cKFSE5ORm1trdLNIju6d9b24YcfYsiQIZg6darC\nLaK/y2w245133kFWVhaKiopw4sQJ1NbWYvny5di8eTNSUlJQXt70kQ73fg+GDBmCXbt2ISUlBWPH\njuUwlsLOnTuHAQMGNFveqVMnrF+/HikpKfjyyy+RkJAg/ezy5cuYPHkyMjMz0aVLFxw4cAAAEBwc\njD179sBkMqFXr17Ys2cPAGD16tWYNGkS0tPT4eXlJW1Hr9e3uA9RsCdHUC11R2o0GsybNw8GgwFH\njhxBZmYmMjMz8fXXX7dxC6m1PawL+qWXXkJOTg5mzJjBM3cHN2jQIHTr1g0AEBAQgOLiYri4uMDX\n1xe+vr4AgLCwMOzatavZuteuXcOiRYtQWloKi8WCnj17tmnb6dFYrVYkJibi559/hlarRWlpKW7c\nuAEA8PHxQb9+/QAAAwYMQHFxMYCGYa5PP/0UFRUVqKmpwfDhwwEAJ06ckOZehoeHY+3atQAapi/I\n7aNr165t/XHthj05gnJzc8Pt27ebLLt16xbc3NwAAL6+voiJicH27dtRWFjY7L3keFo65u7u7gCA\n0NBQxMTEYNasWaiurlaiidRKOnToINU6nU56Rtmj3Nt11apVmDJlCjIyMrBy5Urcvdu2T8impvr0\n6YO8vLxmyzMyMnDz5k2YTCaYTCZ4eHhIx6pjx47S+3Q6HSwWCwAgPj4eK1asQEZGBubPny+9X6PR\nyJ4E/dU+RMGQIygXFxd069YNubm5ABr+2B0+fBiBgYH44YcfpPddvHgROp0OTz31lFJNpVbyV8f8\nnmnTpmHYsGFYsGAB6urqlGoqPYGHBZhevXrh6tWrKCoqAgDs27dP9n1VVVVSLxCvsFPesGHDUFdX\nh927d0vLCgsLUVxcDA8PD2i1WuTm5uLq1asP3VZ1dTU8PT1RV1fX5OGsgwcPRmZmJgAgPT1dWl5Z\nWfnY+3A0DDkCS0hIwIYNGxAREYHp06dj4cKF8PX1RVpaGkJCQmA0GrFkyRKsXbtWVbPtRdbSMW9s\n8eLF6N69O5YsWaJQK+lJ/NUQNNBwdr9y5UrMnj0bkZGRLQ45zJ8/H3FxcRg/fjyHLduJpKQkHDly\nBKNHj4bBYMDHH3+MV155BXl5eQgLC0N6evojXSASFxeHqKgovPrqq+jVq5e0fOnSpdi5cyfCwsJQ\nVlYmLTcYDI+9D0fDZ1cRERGRkNiTQ0REREJiyCEiIiIhMeQQERGRkBhyiIiISEgMOURERCQkhhwi\nIiISEh/rQETtgsViwfr165GVlYVOnTpBp9Nh6NChWLx4MXQ6XavuKzU1FYMHD7bbU56JqH1gyCGi\nduHtt99GbW0tTCYTnJ2dYbVasXfvXtTW1sLZ2blV95WSkgIPD48WQ47VaoVWy45uIkfHbzERKe7S\npUvIycnB+++/LwUarVaLqKgo6PV6JCQkwGAwwGAwICEhQXrEwZQpU5o8pqTx6ylTpuDf//43Jk2a\nhNGjRyMxMRFAQ8DJy8vDe++9B6PRiKNHjyI1NRXTp0/HggULYDAYcPbsWRgMhiZtDA8Px8mTJ9vi\nn4OIWgl7cohIcfn5+Xj22WfRuXPnZj9LTk5GYWEhTCYTbDYbYmNjkZycjJiYmIdu9/r169i5cyfu\n3LmDUaNGYcKECYiMjERqaipiY2Px8ssvA2gYvjp16hTS09Olp3K7urri+PHjGDJkCI4fPw6dTocX\nXnihdT84EdkVe3KIqF07evQojEYjdDodnJycEBkZiZ9++umR1g0JCQEAdO7cGb1798bly5dbfG9g\nYKAUcABg8uTJ2LFjBwBg586dmDRp0t/4FESkBIYcIlJc//79cfHiRVRWVj7Wek5OTrBardLr2tra\nJj/X6/VSrdVqUV9f3+K2XFxcmrwOCQnBqVOnUFBQgGPHjjUbviKi9o8hh4gU5+/vj6CgICxfvhxV\nVVUAGib/7t69G0OHDoXJZILFYkFdXR1MJhOGDx8OAPDz88OZM2cAAOfPn0dBQcEj7a9z584PDVT3\neo3mzp0Lg8HQJDARkWNgyCGidiEhIQF+fn6IjIyEwWBAWFgYfv/9d0RHR6Nv374wGo2IjIxEQEAA\noqKiAACxsbH4/vvvERYWhq1bt6J///7S9jQaTZPtN349ceJEJCUlSROPWxIVFYXS0lIOVRE5KI3t\n3mUKRETURFpaGvbv34/PP/9c6aYQ0RPg1VVERDJmzpyJK1euYMOGDUo3hYieEHtyiIiISEick0NE\nRERCYsghIiIiITHkEBERkZAYcoiIiEhIDDlEREQkJIYcIiIiEtL/A4HTSVGYyr1RAAAAAElFTkSu\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f47553d3a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "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_to_spend_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": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}