Leisure vs Money plotting

leisure.py

#!/usr/bin/env python
"""
Leasure vs Money
Inspiration
Tweet by Stanford Econ Policy https://twitter.com/SIEPR/status/702637668883152896

Data sources
* GDP per capita PPP: : World Bank http://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD?display=default
* GDP per capita current USD: World Bank http://data.worldbank.org/indicator/NY.GDP.PCAP.CD/countries?display=default
* Working hours: OECD.stat https://stats.oecd.org/Index.aspx?DataSetCode=ANHRS
"""
import csv
from matplotlib import pyplot as pl

############
### Settings
############
year = 2014

workdatafile = "ANHRS_25022016071232431.csv"
## GDP/capita in USD
#gdpdatafile = "9e7e9b0e-aa8e-4354-bbd1-e7dbe8c49f17_v2.csv"
## PPP corrected GDP/capita in USD
gdpdatafile = "3b5b9aa4-2235-4a76-b91a-839614e2870b_v2.csv"

normalizecountry = "USA"
#############


## Helper vars
countrydata = {}
normalizer = 1

## Work hours
with open(workdatafile, 'r') as csvfile:
    workreader = csv.reader(csvfile, delimiter=',', quotechar='"')
    for row in workreader:
        try:
            if row[3] == "Total employment" and int(row[6]) == year:
                countrydata[row[0]] = [float(row[14])]
        except:
            pass

## GDP
with open(gdpdatafile, 'r') as csvfile:
    gdpreader = csv.reader(csvfile, delimiter=',', quotechar='"')
    for row in gdpreader:
        columnnum = -1
        if len(row)> 5 and row[0] == "Country Name":
            for i, c in enumerate(row):
                try:
                    if int(c) == year:
                        columnum = i
                        break
                except:
                    continue
        try:
            if row[1] in countrydata:
                countrydata[row[1]] += [float(row[i])]
                if row[1] == normalizecountry:
                    normalizer = float(row[i])
        except:
            pass

## Double-check results by printing them
print(countrydata)

# Plotting data
fig = pl.figure()
ax = fig.add_subplot(111)
for country in countrydata:
    try:
        x, y, t = countrydata[country][1]/normalizer, countrydata[country][0], country
        ax.plot(x, y, 'ko')
        ax.annotate(t, xy=(x, y), xytext=(x+0.02, y))
    except IndexError:
        pass
pl.title('Leisure vs. Money (quick redux)')
pl.ylabel('Hours worked per year [OECD]')
pl.xlabel('GDP per capita (normalized to {}) [World Bank]'.format(normalizecountry))
pl.grid()
pl.savefig("Leasure_vs_Money.png")
pl.show()