Sort CSV using a key computed from two columns, grab first n largest values

Question

Python amateur here...let\'s say here I have snippet of an example csv file:

Country, Year, GDP, Population
Country1         


        

Answer 1

The relevant modules would be:

• csv for parsing the input
• collections.namedtuple to name the fields
• the filter() function to extract the specified year range
• heapq.nlargest() to find the largest values
• pprint.pprint() for nice output

Here's a little bit to get you started (I would do it all but what is the fun in having someone write your whole program and deprive you of the joy of finishing it):

from __future__ import division
import csv, collections, heapq, pprint

filecontents = '''\
Country, Year, GDP, Population
Country1,2002,44545,24352
Country2,2004,14325,75677
Country3,2004,23132412,1345234
Country4,2004,2312421,12412
'''

CountryStats = collections.namedtuple('CountryStats', ['country', 'year', 'gdp', 'population'])
dialect = csv.Sniffer().sniff(filecontents)

data = []
for country, year, gdp, pop in csv.reader(filecontents.splitlines()[1:], dialect):
    row = CountryStats(country, int(year), int(gdp), int(pop))
    if row.year == 2004:
        data.append(row)

data.sort(key = lambda s: s.gdp / s.population)
pprint.pprint(data)