A seasonal subseries plot facets the time series by each season in the seasonal period. These facets form smaller time series plots consisting of data only from that season. If you had several years of monthly data, the resulting plot would show a separate time series plot for each month. The first subseries plot would consist of only data from January. This case is given as an example below.

gg_subseries(data, y = NULL, period = NULL, ...)



A tidy time series object (tsibble)


The variable to plot (a bare expression). If NULL, it will automatically selected from the data.


The seasonal period to display.


Additional arguments passed to geom_line()


The horizontal lines are used to represent the mean of each facet, allowing easy identification of seasonal differences between seasons. This plot is particularly useful in identifying changes in the seasonal pattern over time.

similar to a seasonal plot (gg_season()), and


Hyndman and Athanasopoulos (2018) Forecasting: principles and practice, 2nd edition, OTexts: Melbourne, Australia. https://OTexts.org/fpp2/


library(tsibble) library(dplyr) tsibbledata::aus_retail %>% filter( State == "Victoria", Industry == "Cafes, restaurants and catering services" ) %>% gg_subseries(Turnover)