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Data Analytics in Python

Getting the Data and Visualizing Datasets Using Scatter Plots

Explore how to obtain and clean GDP and economic freedom datasets, merge them using Python and Pandas, and create scatter plots to visualize the relationship between economic freedom scores and GDP per capita. Understand data cleaning challenges and improve plot clarity to identify trends and outliers.

We'll cover the following...

Get the data

You can get up-to-date GDP data by country from many sources. We’ll want our data broken down to the per capita level because that’s the best way to get valuable apples-to-apples comparisons between countries of different sizes.

Get data from the World Bank site

We got our GDP data from the World Bank’s site and our Index of Economic Freedom data from here. Here’s how all the basic setup works.

Python 3.5
import pandas as pd
import numpy as np
import matplotlib as plt
import matplotlib.pyplot as plt
gdp = pd.read_csv('WorldBank_per_capita_GDP.csv')
ec_index = pd.read_csv('economicdata.csv')
print (gdp)

Running GDP shows us that the GDP data set has 248 rows that include plenty of ...