In this chapter, we examined various techniques for grouping and analyzing groups of data with pandas. An introduction to the split-apply-combine pattern for data analysis is given, along with an explanation of how this pattern is implemented in pandas. We also covered how to make transformations of grouped data and how to filter out groups of data based on results of functions that you can provide to pandas. Finally, we covered how to convert data into discrete intervals and analyze the results.

In the next chapter, we will take what you learned up to this point and get into some of the most interesting capabilities of pandas (at least in my opinion): the analysis of time-series data.