Fixed length of aggregate dataframes with missing data

I’ve been using the retrieve_dataframe function in cognite-sdk and been missing the feature to getting a fixed size of the dataframe when doing separate requests. When requesting aggregates of data points in a timeseries, there is no output when the are no data points within a instance of granularity. For example, I have used:

df = cdfClientRef.datapoints.retrieve_dataframe(external_id = '', start = '10d-ago', end = 'now', aggregates = ['average'], granularity = '1d')

If there are no data points in that time I get an empty dataframe. If there are no data points within a day in this example that row would missing from the output.

Empty DataFrame

Columns: [ |average]

Index: []
 

If I instead request several timeseries, the missing data is given as NaN to fill out the dataframe:

                     |average        |average

2022-08-30                NaN        3803.468955

2022-08-31                NaN        3837.437594

2022-09-01                NaN        3826.125239

2022-09-02                NaN        3841.227053

2022-09-03                NaN        3834.526855

2022-09-04                NaN        3839.324081

2022-09-05                NaN        3829.446260

2022-09-06                NaN        3833.002560

2022-09-07                NaN        3853.340727

2022-09-08                NaN        3854.664126
 

It would be useful with an option to make sure the output dataframe contains an entry for each requested instance for a given granularity, meaning that instead of an empty dataframe the output would be:

                     |average

2022-08-30                NaN

2022-08-31                NaN

2022-09-01                NaN

2022-09-02                NaN

2022-09-03                NaN

2022-09-04                NaN

2022-09-05                NaN

2022-09-06                NaN

2022-09-07                NaN

2022-09-08                NaN