Summary

In this chapter, we have seen the importance of creating meaningful and interesting visualizations when analyzing data. A good data visualization can immensely help the analyst's job, representing data in a way that can reach larger audiences and explain concepts that could be hard to translate into words or to represent with tables.

A graph, to be effective as a data visualization tool, must show the data, avoid distortions, make understanding large datasets easy, and have a clear purpose, such as description or exploration. The main goal of a graph is to communicate data, so the analyst must keep that in mind when creating a graph. A useful graph is more desirable than a beautiful one.

We demonstrated some kinds of graphs commonly used in analysis: the line graph, the scatter plot, the histogram, and the boxplot. Each graph has its purpose and application, depending on the data and the goal. We have also shown how to create graphs directly from Matplotlib, from pandas, or a combination...