Demographics¶

In this exercise, you will use comprehensions to convert, filter and analyze JSON data. The data in the file population.json contains the population of all the countries in the world and their population.

Exercise 1: Read the data¶

Get started by reading the data in population.json and display the first records:

import json
from pprint import pprint

pop = json.load(open("population.json"))
pprint(pop[:3])

Exercise 2: Countries¶

Write code for the following tasks

extract a list of all countries.
extract unique countries only.
print the number of unique countries.

Exercise 3: Filter¶

Calculate the total sum of the population in 1961 and 2010.

Note

There might be some overlaps in the data such as East Germany and Germany, so the overall sum will be higher than the actual world population.

Exercise 4: Nested List¶

Convert the data to a nested list with the columns country, continent, population for the year 2010:

[['Afghanistan', 'Asia', 27962207.0],
['Albania', 'Europe', 2901883.0],
['Algeria', 'Africa', 36036159.0]]

Exercise 5: Dictionary¶

Convert the nested list back to a dictionary with the key being the country name and the value a dictionary of the other values:

{
    'Afghanistan': {'population': 27962207.0, 'continent': 'Asia'},
    'Albania': {'population': 2901883.0, 'continent': 'Europe'},
    'Algeria': {'population': 36036159.0, 'continent': 'Africa'},
}

Exercise 6: Transpose¶

Create a dictionary, but this time it should contain three lists:

{
    ['Afghanistan', 'Albania', 'Algeria', ...],
    ['Asia', 'Europe', 'Africa', ...],
    [27962207.0, 2901883.0, 36036159.0, ...],
}