Summary

In this chapter, we introduced popular techniques for the visual exploration of time series data. We started from a line plot, which shows simple dynamics of time series, and moved on to a lag plot to explore the relationship between past and current values. After that, we compared seasonal cycles in parallel in a seasonal plot, and finally, we inspected the variability of a time series in a box plot.

You learned how to interpret the dynamics in these plots and how they enrich your understanding of time series. You also learned how to implement these visualization techniques in KNIME Analytics Platform.

These visualizations appear in the data exploration phase of most time series analysis applications. You will need them to inspect whether the time series is periodic or shows a trend, to evaluate the model fit of an AR model, to obtain the best seasonal lag for prediction and missing value replacement, to assess the type of seasonality, and to visually evaluate the stationarity...