income-software-engineers-countries.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# What Software Engineers Earn Compared to the General Population"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook we'll compare the median annual income of software engineers to the average annual income (GDP per Capita) in 50 countries. It's shown how to scrape the data from a web page using [lxml](http://lxml.de/), turn it into a [Pandas](http://pandas.pydata.org/) dataframe, clean it up and create scatter and bar plots with [matplotlib](http://matplotlib.org/) to visualize the general trend and see which countries are the best and worst for software engineers based on how much they earn compared to the average person.\n",
    "\n",
    "The data comes from [PayScale](http://www.payscale.com/) and the [International Monetary Fund](http://www.imf.org/) and was published by [Bloomberg](http://www.bloomberg.com/visual-data/best-and-worst/highest-paid-software-engineers-countries) in May 2014. It includes figures for 50 countries for which data was most available to PayScale. The software engineer figures represent income data collected from May 1, 2013, to May 1, 2014, and use exchange rates from May 5, 2014. The median years of work experience for survey respondents from each country range from two to five years.\n",
    "\n",
    "## Setup\n",
    "\n",
    "First we load the necessary libraries, set the plot style and some variables, including a [geonamescache](https://github.com/yaph/geonamescache) object for adding country codes used to link geographic data with income figures in this [interactive map](https://ramiro.org/map/world/income-software-engineers-countries/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%load_ext signature\n",
    "%matplotlib inline\n",
    "\n",
    "import os\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "import geonamescache\n",
    "\n",
    "from lxml import html\n",
    "\n",
    "mpl.style.use('ramiro')\n",
    "\n",
    "data_dir = os.path.expanduser('~/data')\n",
    "gc = geonamescache.GeonamesCache()\n",
    "\n",
    "chartinfo = '''Figures represent income data from May 2013 to May 2014 using exchange rates from May 2014. Average annual income figures are for 2014.\n",
    "Author: Ramiro Gómez - ramiro.org • Data: Bloomberg/PayScale - bloomberg.com/visual-data/best-and-worst/highest-paid-software-engineers-countries'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data retrieval and cleanup\n",
    "\n",
    "To scrape the data from the web page, I looked at the source to determine a way to identify the data table. It is the only table on the page with a class of `hid` so the xpath expression below can be used to extract the table from the HTML source after it was loaded."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "url ='http://www.bloomberg.com/visual-data/best-and-worst/highest-paid-software-engineers-countries'\n",
    "xpath = '//table[@class=\"hid\"]'\n",
    " \n",
    "tree = html.parse(url)\n",
    "table = tree.xpath(xpath)[0]\n",
    "raw_html = html.tostring(table)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pandas makes it easy to turn this raw HTML string into a dataframe. We instruct it to use the `Rank` column as the index and the first row as the header. The [read_html](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_html.html) function returns a list, in our case of one dataframe object, so we just grab this and print the first few rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Ratio of median software engineer pay to average income</th>\n",
       "      <th>Median annual pay for software engineers</th>\n",
       "      <th>Average annual income</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Pakistan  t</td>\n",
       "      <td>5.56</td>\n",
       "      <td>$7,200</td>\n",
       "      <td>$1,296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>India  t</td>\n",
       "      <td>3.91</td>\n",
       "      <td>$6,200</td>\n",
       "      <td>$1,584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>South Africa  t</td>\n",
       "      <td>3.64</td>\n",
       "      <td>$24,000</td>\n",
       "      <td>$6,595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bulgaria  t</td>\n",
       "      <td>3.28</td>\n",
       "      <td>$25,200</td>\n",
       "      <td>$7,682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>China  t</td>\n",
       "      <td>3.15</td>\n",
       "      <td>$23,100</td>\n",
       "      <td>$7,333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Country  \\\n",
       "Rank                    \n",
       "1         Pakistan  t   \n",
       "2            India  t   \n",
       "3     South Africa  t   \n",
       "4         Bulgaria  t   \n",
       "5            China  t   \n",
       "\n",
       "      Ratio of median software engineer pay to average income  \\\n",
       "Rank                                                            \n",
       "1                                                  5.56         \n",
       "2                                                  3.91         \n",
       "3                                                  3.64         \n",
       "4                                                  3.28         \n",
       "5                                                  3.15         \n",
       "\n",
       "     Median annual pay for software engineers Average annual income  \n",
       "Rank                                                                 \n",
       "1                                      $7,200                $1,296  \n",
       "2                                      $6,200                $1,584  \n",
       "3                                     $24,000                $6,595  \n",
       "4                                     $25,200                $7,682  \n",
       "5                                     $23,100                $7,333  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_html(raw_html, header=0, index_col=0)[0]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and the data types that were automatically determined by Pandas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country                                                     object\n",
       "Ratio of median software engineer pay to average income    float64\n",
       "Median annual pay for software engineers                    object\n",
       "Average annual income                                       object\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The output above shows, that we need to do some cleanup before continuing with further exploration. The values in the `Country` column all end in a space followed by a t, which we just remove. Also we need to turn the dollar amounts into a numeric type for use in calculations and plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country                                                     object\n",
       "Ratio of median software engineer pay to average income    float64\n",
       "Median annual pay for software engineers                     int64\n",
       "Average annual income                                        int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Country'] = df['Country'].apply(lambda x: x.rstrip('t').strip())\n",
    "\n",
    "for col in df.columns[2:]:\n",
    "    df[col] = pd.to_numeric(df[col].apply(lambda x: x.lstrip('$').replace(',', '')))\n",
    "\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This looks better now. As a sanity check we can test whether the ratio that is contained in the data agrees with the income numbers. To do so we calculate the ratio ourselves and compare it to the existing one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratio = round(df['Median annual pay for software engineers'] / df['Average annual income'], 2)\n",
    "all(ratio == df['Ratio of median software engineer pay to average income'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploration and visualization\n",
    "\n",
    "### Income comparison\n",
    "\n",
    "To get a holistic view we first create a scatter plot with all 50 records showing the median software engineer income on the X axis and the annual average of the whole population on the Y axis. We also draw a quadratic polynomial fitting curve to see if we can spot a trend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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T+7N7927lBFBzur7Cp6enG1R4fcJRs+Iaa6A14w0LCzOY3tTExNSYW5qYyLIsNm/erEwr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\nw4YV4LTDRZdC95RQRyQi0mYBbxecn5/PtddeS5c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kJPD1118HOxYRkbNmPfoL0/G/QOnp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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa2ab6d66a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = 'Median annual pay for software engineers'\n",
    "y = 'Average annual income'\n",
    "title = 'Median annual income of software engineers vs. general average in 50 countries'\n",
    "\n",
    "fig = plt.figure(figsize=(11, 9))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.plot(x, y, '.', data=df, ms=10, alpha=.7)\n",
    "ax.set_title(title, fontsize=20, y=1.04)\n",
    "ax.set_xlabel(x)\n",
    "ax.set_ylim(bottom=0, top=101000)\n",
    "ax.set_ylabel(y)\n",
    "\n",
    "# Polynomial curve fitting \n",
    "# http://docs.scipy.org/doc/numpy/reference/routines.polynomials.classes.html\n",
    "polynomial = np.polynomial.Polynomial.fit(df[x], df[y], 2)\n",
    "xp = np.linspace(0, 120000, 100)\n",
    "yp = polynomial(xp)\n",
    "ax.plot(xp, yp, '-', lw=1, alpha=.5)\n",
    "\n",
    "fig.text(0, -.04 , chartinfo, fontsize=11)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before interpreting this and the following plots, I'll point out a few issues with the data. We do not know how many respondents took part in the PayScale survey and we do know that their work experiences range from two to five years. Whether this sample is a good representation for the income of software engineers in the respective countries is questionable.\n",
    "\n",
    "Moreover, we compare median annual values for software engineers with mean annual values for the general population. Considering [how large the income share of top earners](https://ramiro.org/notebook/top-incomes-share/) is in several countries, annual median values for the general population might well show a different picture.\n",
    "\n",
    "With this in mind, software engineer looks like a good career choice in the majority of the 50 countries. In some of the countries we see in the lower left, mid-level software engineers earn multiples of what the average person does. But there are also countries, where software engineers earn a lot less. To find out which are the best and worst countries for software engineers with respect to income, we'll plot rankings in form of bar plots next.\n",
    "\n",
    "### Country rankings\n",
    "\n",
    "In the following bar plot countries are ranked by the ratio of median software engineer pay to average income. Since our dataframe is already ordered by the ratio from high to low, we can simply use the head and tail methods to get the slices we want to show."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "col = 'Ratio of median software engineer pay to average income'\n",
    "title = 'Best and worst countries ranked by ratio of median software engineer pay to average income'\n",
    "limit = 10\n",
    "\n",
    "best = df.head(limit)[::-1]\n",
    "worst = df.tail(limit)\n",
    "ticks = np.arange(limit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we create a plot consisting of two bar charts showing the best countries for software engineers on the left and the worst on the right based on income ratio. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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EIrmOBjds2IBZs2Yp7eCrKfm9Kce8vnVVrW8aoqenJ9ep071798BxHOzs7FRa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lAAAg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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa2a95ea710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14, 5))\n",
    "fig.suptitle(title, fontsize=20)\n",
    "\n",
    "ax1 = fig.add_subplot(1, 2, 1)\n",
    "ax1.barh(ticks, best[col], alpha=.5, color='#00ff00')\n",
    "ax1.set_yticks(ticks)\n",
    "ax1.set_yticklabels(best['Country'].values, fontsize=15, va='bottom')\n",
    "\n",
    "ax2 = fig.add_subplot(1, 2, 2)\n",
    "ax2.barh(ticks, worst[col], alpha=.5, color='#ff0000')\n",
    "ax2.set_yticks(ticks)\n",
    "ax2.set_yticklabels(worst['Country'].values, fontsize=15, va='bottom')\n",
    "\n",
    "fig.text(0, -.07, chartinfo, fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This chart again shows that the income differences are huge in some countries and that software engineers are likely to earn more. In our dataset Pakistan and India are the two countries with the lowest average annual income and Qatar has the 2nd highest average income after Norway. I assume that the income distribution in countries with a high ratio is skewed towards lower incomes and in countries with low ratios towards higher incomes. Again, it'd be interesting to compare medians to medians and not medians to means, but we'd have to find another data source for such a comparison.\n",
    "\n",
    "## Adding country codes\n",
    "\n",
    "In this last short section, I'll show how to add [ISO 3](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3) country codes to our dataset in order to visualize the data in an [interactive D3.js based map](https://ramiro.org/map/world/income-software-engineers-countries/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Ratio of median software engineer pay to average income</th>\n",
       "      <th>Median annual pay for software engineers</th>\n",
       "      <th>Average annual income</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rank</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Pakistan</td>\n",
       "      <td>5.56</td>\n",
       "      <td>7200</td>\n",
       "      <td>1296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>India</td>\n",
       "      <td>3.91</td>\n",
       "      <td>6200</td>\n",
       "      <td>1584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>South Africa</td>\n",
       "      <td>3.64</td>\n",
       "      <td>24000</td>\n",
       "      <td>6595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bulgaria</td>\n",
       "      <td>3.28</td>\n",
       "      <td>25200</td>\n",
       "      <td>7682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>China</td>\n",
       "      <td>3.15</td>\n",
       "      <td>23100</td>\n",
       "      <td>7333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country  Ratio of median software engineer pay to average income  \\\n",
       "Rank                                                                          \n",
       "1         Pakistan                                               5.56         \n",
       "2            India                                               3.91         \n",
       "3     South Africa                                               3.64         \n",
       "4         Bulgaria                                               3.28         \n",
       "5            China                                               3.15         \n",
       "\n",
       "      Median annual pay for software engineers  Average annual income  \n",
       "Rank                                                                   \n",
       "1                                         7200                   1296  \n",
       "2                                         6200                   1584  \n",
       "3                                        24000                   6595  \n",
       "4                                        25200                   7682  \n",
       "5                                        23100                   7333  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_map = df.copy()\n",
    "names = gc.get_countries_by_names()\n",
    "df_map['iso3'] = df_map['Country'].apply(lambda x: names[x]['iso3'])\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we use the geonamescache object initialized in the beginning to get a dictionary of countries keyed by names. The values are dictionaries as well, which, among other things, contain ISO 3 country codes. Finally, to save a few bytes the country column is removed and the dataframe saved as a CSV file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "del df_map['Country']\n",
    "df_map.to_csv(data_dir + '/economy/income-software-engineers-countries.csv', encoding='utf-8', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "In this notebook we looked at income data for software engineers in 50 countries and compared their earnings to the general population. In the process we scraped the dataset from the source web page, cleaned it up, visualized it and interpreted the results pointing out potential issues with the dataset and methodology.\n",
    "\n",
    "While software engineer seems to be a good career choice in most of the countries, keep the caveats in mind before you start making emigration plans. Also, income should certainly not be your only criterion for choosing a profession or a place to live in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "Author: <a href=\"https://ramiro.org/\">Ramiro Gómez</a>\n",
       "            • Last edited: April 08, 2016<br>Linux 4.2.0-35-generic - CPython 3.5.1 - IPython 4.1.2 - matplotlib 1.5.1 - numpy 1.10.4 - pandas 0.18.0"
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     "execution_count": 12,
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     "output_type": "execute_result"
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