Why dd.repartition() is using round divisions

Dask DataFrame
1

I am wondering why repartition(freq='24h') is resulting in round divisions.

Dask dataframe with divisions aligned on 12:00:00

df = dask.datasets.timeseries().compute()
df.index += pd.to_timedelta('12:00:00')
dd = dask.dataframe.from_pandas(df, npartitions=15)
dd

image

repartition(freq=‘24h’) is resulting in round divisions:

dd.repartition(freq='24h')

image

Expected result

image

Same happens with '1d' and pd.to_timedelta('1d') because Dask repartition_freq() explicitly ceils the first division, but I am unable to understand why it’s a good idea, and how can I bypass this?

def repartition_freq(df, freq=None):
    [...]
    try:
        start = df.divisions[0].ceil(freq)
    except ValueError:
        start = df.divisions[0]