Set start value of Timestamp column in resample and interpolate

[pintbry]

My tempo tsdf has timestamp column data starting from 2023-02-01 00:00:00 which has tag data for each second. I am trying to aggregate this data on a hourly basis using resample and interpolate but while doing via both these options the timestamp column shows data starting from the previous day 2023-01-31 23:30:00 and the next 1 hour.
PS: I do not have any data of the previous day in my original data frame.
However I want to enforce the start time from what is in my dataset 2023-02-01 00:00:00.

Do we have a provision to enforce this? Believe it is similar to loffset of pandas.

`
tempo_tsdf = TSDF(csvdata_df, ts_col="TimeStampUTC", partition_cols = ["Day"])
#Using interpolate
tempo_tsdf.interpolate(
freq="hr",
func="mean",
target_cols= ["tag"],
method="linear"
)

#using resample
tempo_tsdf.resample(freq='hr', func='mean')
`