In this chapter, we examined many of the ways to represent events that occur at specific points in time and how to model these values as they change over time. This involved learning many capabilities of pandas including date and time objects, representation of changes in time with intervals and periods, and performing several types of operations on time series data such as frequency conversion, resampling, and calculating rolling windows.
In the remaining two chapters of this book, we will leave the mechanics of pandas behind and look more into both visualization of data and applying pandas to analysis of financial data.