Plotting a histogram

Statistical Thinking in Python (Part 1)

Justin Bois

Teaching Professor at the California Institute of Technology

2008 US swing state election results

Data retrieved from Data.gov (https://www.data.gov/)

ch1-2.003.png

Generating a histogram

import matplotlib.pyplot as plt
_ = plt.hist(df_swing['dem_share'])
_ = plt.xlabel('percent of vote for Obama')
_ = plt.ylabel('number of counties')
plt.show()

Always label your axes

2008 US swing state election results

Data retrieved from Data.gov (https://www.data.gov/)

ch1-2.013.png

Histograms with different binning

Data retrieved from Data.gov (https://www.data.gov/)

ch1-2.015.png

Setting the bins of a histogram

bin_edges = [0, 10, 20, 30, 40, 50,
                60, 70, 80, 90, 100]
_ = plt.hist(df_swing['dem_share'], bins=bin_edges)
plt.show()

ch1-2.022.png

Setting the bins of a histogram

_ = plt.hist(df_swing['dem_share'], bins=20)
plt.show()

ch1-2.027.png

Seaborn

An excellent Matplotlib-based statistical data visualization package written by Michael Waskom

Setting Seaborn styling

import seaborn as sns
sns.set()
_ = plt.hist(df_swing['dem_share'])
_ = plt.xlabel('percent of vote for Obama')
_ = plt.ylabel('number of counties')
plt.show()

A Seaborn-styled histogram

ch1-2.038.png

¹ Data retrieved from Data.gov (https://www.data.gov/)

Let's practice!

Statistical Thinking in Python (Part 1)