As we saw in the previous chapter, pandas provides implementations for most visualizations we would want to create; however, there is another library, seaborn, which 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. While seaborn offers alternatives to many of the plot types we covered in the previous chapter, for the most part, we will only cover new types that seaborn makes possible and leave learning about the rest as an exercise. Additional available functions using the seaborn API can be found at https://seaborn.pydata.org/api.html.
For this section, we will be working with the 1-introduction_to_seaborn.ipynb notebook. First, we must import seaborn...
