Whew, that was a lot! We learned how to create impressive and customized visualizations using matplotlib, pandas, and seaborn. We discussed how we can use seaborn for additional plotting types and cleaner versions of some familiar ones. Now we can easily make our own colormaps, annotate our plots, add reference lines and shaded regions, finesse the axes/legends/titles, and control most aspects of how our visualizations will appear. We also got a taste of working with itertools and creating our own generators.
Take some time to practice what we've discussed with the following exercises. In the next chapter, we will apply all that we have learned to finance, as we build our own Python package and compare bitcoin to the stock market.
