Sometimes data sorted into time buckets can have gaps. This can happen if you have irregular sampling intervals, or you have experienced an outage of some sort. If you have a time bucket that has no data at all, the average returned from the time bucket is NULL, which could cause problems. You can use a gapfilling function to create additional rows of data in any gaps, ensuring that the returned rows are in chronological order, and contiguous. The time bucket gapfill function creates a contiguous set of time buckets but does not fill the rows with data. You can create data for the new rows using another function, such as last observation carried forward (LOCF), or interpolation.
For more information about gapfilling and interpolation API calls, see the hyperfunction API documentation.
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