Signal processing is a field of engineering and applied mathematics that analyzes analog and digital signals, corresponding to variables that vary with time. One of the categories of signal processing techniques is time series analysis. A time series is an ordered list of data points starting with the oldest measurements first. The data points are usually equidistant, for instance, consistent with daily or annual sampling. In time series analysis, the order of the values is important. It's common to try to derive a relation 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.

The time series examples in this chapter use annual sunspot cycles data. This data is provided by the statsmodels package (an open source Python project). The examples use NumPy/SciPy, pandas, and also statsmodels.

We will cover the following topics in this chapter: