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Data Analytics in Python

US State Incomes and Literacy Rates

Learn to analyze the relationship between literacy rates and income levels across US states using Python. This lesson guides you through importing data, classifying incomes by quantiles, merging datasets, and creating plots. Understand why literacy may correlate with income rather than cause differences in economic groups.

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US Literacy rates

Now let’s look at a smaller scale and compare literacy rates and income for each US state. The data for literacy rates of US states has been taken from the ThinkImpact website. Please run the following code to see it yourself.

Python 3.5
import pandas as pd
import matplotlib as plt
import numpy as np
df = pd.read_csv('US_literacy_rate_by_states.csv')
df.rename(columns={'Literacy Rate (%)':'Literacy Rate'}, inplace=True)
df = df[['State','Literacy Rate']]
df = df.dropna(subset=['Literacy Rate'])
print (df)

Incomes of each state

The US states income group dataset is taken from ...