Time series represent the time-evolution of a dynamic population or process. They are used to identify, model, and forecast patterns and behaviors in data that is sampled over discrete time intervals.
Consider using timetables instead of
timeseries objects, where you can store time-stamped data as column-oriented data variables. Additionally, you can use time-specific functions to align, combine, and perform calculations with one or more timetables.