Numerical Computing with Python

Visualizing a bivariate distribution

We should bear in mind that the Big Mac index is not directly comparable between countries. Normally, we would expect commodities in poor countries to be cheaper than those in rich ones. To represent a fairer picture of the index, it would be better to show the relationship between Big Mac pricing and Gross Domestic Product (GDP) per capita.

We are going to acquire GDP per capita from Quandl's World Bank World Development Indicators (WWDI) dataset. Based on the previous code example of acquiring JSON data from Quandl, can you try to adapt it to download the GDP per capita dataset?

For those who are impatient, here is the full code:

import urllibimport jsonimport pandas as pdimport timefrom urllib.request ...