Utilizing seaborn for advanced plotting

As we saw in the previous chapter, pandas provides implementations for most visualizations we would want to create; however, there is another library, seaborn, that provides additional functionality for more involved visualizations and makes creating visualizations with long-format data much easier than pandas. These also tend to look much nicer than standard visualizations generated by matplotlib.

For this section, we will be working with the 1-introduction_to_seaborn.ipynb notebook. First, we must import seaborn, which is traditionally aliased as sns:

>>> import seaborn as sns

Let's also import numpy, matplotlib.pyplot, and pandas, and then read in the CSV files for the Facebook stock prices and earthquake data:

>>> %matplotlib inline
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> import pandas as pd 
>>> fb = pd.read_csv(
...     ...