In this chapter, the time series examples used annual sunspot cycles data.

You learned that it's common to try to derive a relationship between a value and another data point or combination of data points a fixed number of periods in the past, in the same time series.

A moving average specifies a window of previously seen data, which is averaged each time the window slides forward by one period. In the pandas API, the rolling_window() function provides the window functions functionality with different values of the win_type string parameter corresponding to different window functions.

Cointegration is similar to correlation and is a metric to define the relatedness of two time series. In regression setups, we frequently encounter the problem of overfitting. This issue arises when we have a perfect fit for a sample, which performs poorly when we introduce new data points. To evaluate a model, we can compute appropriate evaluation metrics.

Databases are an important tool for data analysis. Relational databases have been around since the 1970s. Recently, NoSQL databases have become a viable alternative. The next chapter, Chapter 8, Working with Databases, contains information about the various databases (relational and NoSQL) and related APIs.