Summary
In this chapter, we discussed the most important plots in Python. Different plots suit different purposes, and you should choose them accordingly. The default settings of each plot may not be perfect for your needs, so customizations are necessary. You also learned the importance of choosing the right geometries and aesthetics to avoid problems in your dataset, such as significant quantity imbalance or highlighting features to make an exploratory argument.
Business queries are the starting point of designing a statistical plot. We discussed the necessity of transforming data to fit a function API and choosing proper plotting functions to answer queries without hassle.
In the next chapter, let's look at some probability distributions. After all, both the histogram plot and the density estimation plot in a joint plot try to uncover the probability distributions behind the dataset.
