Seasonality, as we saw in the previous chapter, is one of the main components of time series data. Furthermore, this component, when existing in a series, plays a pivotal role in the forecasting process of the future values of the series, as we will see in the coming chapters, since it contains structural patterns. In this chapter, we will focus on methods and approaches for identifying and then classifying the seasonal patterns of a series. This includes the use of descriptive statistics tools, such as summary statistics, as well as data visualization methods, utilizing packages such as dplyr, ggplot2, plotly, forecast, and TSstudio.
In this chapter, we will cover the following topics:
- Single and multiple seasonality patterns
- Descriptive statistic methods to identify seasonality patterns
- Data visualization tools to explore and identify seasonality patterns...
