I have two timeseries that I got from a feather
file.
One series turned into dtype
datetime64[ns]
the other turned into datetime64[ns, UTC]
as the formats are different I can't run pd.merge
how can I fix this?
pd.to_datetime(column, utc=False)
doesn't seem to do it?
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cel
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KillerSnail
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1 Answers
4
I'm still looking for other answers...
However, this works:
Consider the time series ts
ts = pd.date_range('2016-03-31', periods=6, freq='4H', tz='Asia/Hong_Kong')
ts
DatetimeIndex(['2016-03-31 00:00:00+08:00', '2016-03-31 04:00:00+08:00',
'2016-03-31 08:00:00+08:00', '2016-03-31 12:00:00+08:00',
'2016-03-31 16:00:00+08:00', '2016-03-31 20:00:00+08:00'],
dtype='datetime64[ns, Asia/Hong_Kong]', freq='4H')
Then strip off timezone information by building from values
pd.to_datetime(ts.values)
DatetimeIndex(['2016-03-30 16:00:00', '2016-03-30 20:00:00',
'2016-03-31 00:00:00', '2016-03-31 04:00:00',
'2016-03-31 08:00:00', '2016-03-31 12:00:00'],
dtype='datetime64[ns]', freq=None)

piRSquared
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