Introduction

Data visualization is a powerful tool that allows users to digest large amounts of data very quickly. There are different types of plots that serve various purposes. In business, line plots and bar graphs are very common to display trends over time and compare metrics across groups, respectively. Statisticians, on the other hand, may be more interested in checking correlations between variables using a scatterplot or correlation matrix. They may also use histograms to check the distribution of a variable or boxplots to check for outliers. In politics, pie charts are widely used for comparing the total data between or among categories. Data visualizations can be very intricate and creative, being limited only by one's imagination.

The Python library Matplotlib is a well-documented, two-dimensional plotting library that can be used to create a variety of powerful data visualizations and aims to "...make easy things easy and hard things possible" (https://matplotlib...