This chapter focused on how to load, visualize, and model time-related data. Although we could not cover all aspects of this challenging topic, we discussed the most widely used smoothing and filtering algorithms, seasonal decompositions, and ARIMA models; we also computed some forecasts and estimates based on these.

The next chapter is somewhat similar to this one, as we will cover another domain-independent area on another important dimension of datasets: instead of when, we will focus on where the observations were captured.