Gapminder data: how has the world changed for 200 years?

Introduction

“Gapminder fights devastating misconceptions about global development. Gapminder produces free teaching resources making the world understandable based on reliable statistics.” — source Gapminder

Gapminder was founded by Hans Roosling along with his son and his daughter-in-law. One of their works was published into a book named “Factfulness” which aims to change the way we look at the world merely by data. In this small project, we will try to look at some of the datasets of Gapminder to discover some interesting facts about the global change from 1800–2000. Here are the questions we have asked ourselves:

• Which region of the world has been changing relatively quickly compared to others in terms of GDP, life expectancy, and other indices?
• How have income, population, child mortality, and children born per woman decide the life expectancy of a certain country?

This is one of my projects in the Udacity Data Analyst Nanodegree program, and it is implemented in Python using popular libraries such as Pandas, Numpy, and Matplotlib. Check the full implementation here.

# Importing neccessary libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
% matplotlib…