Pandas API: to_datetime with unit changes how strings are interpreted

vals = ["2016-01-02 03:04:05"]

pd.to_datetime(vals)  # <- works
pd.to_datetime(vals, unit="s")  # <- raises

vals2 = ["20160102"]

>>> pd.to_datetime(vals2)
DatetimeIndex(['2016-01-02'], dtype='datetime64[ns]', freq=None)
>>> pd.to_datetime(vals2, unit="s")
DatetimeIndex(['1970-08-22 08:01:42'], dtype='datetime64[ns]', freq=None)

if you pass a unit (other than "ns") to to_datetime we go through array_with_unit_to_datetime and cast strings to float instead of trying to parse them. I think it makes more sense to keep the string behavior unchanged and only affect how we treat floats/ints.

Comment From: MarcoGorelli

what's vals2?

Comment From: jbrockmendel

vals2 = ["20160102"], updated.

Comment From: MarcoGorelli

ok yah, +1 for this