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.