This chapter provided a collection of special methods that show the flexibility and usefulness of pandas. This chapter has been like an illustrated glossary in which each function serves a very unique purpose. Now, you should have an idea of how to create and apply one-liner functions in pandas, and you should understand the concepts of missing values and the methods that take care of them. This is also a compendium of all the miscellaneous methods that can be applied to a series and the numeric methods that can be applied to any kind of Python data structure.

In the next chapter, we will take a look at how we can handle time series data and plot it using matplotlib. We will also have a look into the manipulation of time series data by looking at rolling, resampling, shifting, lagging, and time element separation.