Most tutorials on time-series analysis start with the ts function of the stats package, which can create time-series objects in a very straightforward way. Simply pass a vector or matrix of numeric values (time-series analysis mostly deals with continuous variables), specify the frequency of your data, and it's all set!
The frequency refers to the natural time-span of the data. Thus, for monthly data, you should set it to 12, 4 for quarterly and 365 or 7 for daily data, depending on the most characteristic seasonality of the events. For example, if your data has a significant weekly seasonality, which is pretty usual in social sciences, it should be 7, but if the calendar date is the main differentiator, such as with weather data, it should be 365.
In the forthcoming pages, let's use daily summary statistics from the hflights dataset. First let's load the related dataset and transform it to data.table for easy aggregation. We also have to create a date variable...