Plotting Using Seaborn

While matplotlib allows you to plot a lot of interesting charts, it takes a bit of effort to get the chart that you want. This is especially true if you are dealing with a large amount of data and would like to examine the relationships between multiple variables.

Introducing Seaborn, a complementary plotting library that is based on the matplotlib data visualization library. Seaborn's strength lies in its ability to make statistical graphics in Python, and it is closely integrated with the Pandas data structure (covered in Chapter 3). Seaborn provides high‐level abstractions to allow you to build complex visualizations for your data easily. In short, you write less code with Seaborn than with matplotlib, while at the same time you get more sophisticated charts.

Displaying Categorical Plots

The first example that you will plot is called a categorical plot (formerly known as a factorplot). It is useful in cases when you want to plot the distribution...