I am trying to have a vector of seconds between two time intervals:
import numpy as np import pandas as pd date="2011-01-10" start=np.datetime64(date+'T09:30:00') end=np.datetime64(date+'T16:00:00') range = pd.date_range(start, end, freq='S')
For some reason when I print range
I get:
[2011-01-10 17:30:00, ..., 2011-01-11 00:00:00]
So the length is 23401 which is what I want but definitely not the correct time interval. Why is that?
Also, if I have a DataFrame df
with a column of datetime64 format that looks like:
Time 15:59:57.887529007 15:59:57.805383290
Once I solved the problem above, will I be able to do the following:
data = df.reindex(df.Time + range) data = data.ffill()
??
I need to do the exact steps proposed here except with datetime64
format. Is it possible?
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Answer
It seems that pandas date_range
is dropping the timezone (looks like a bug, I think it’s already filed…), you can use Timestamp rather than datetime64 to workaround this:
In [11]: start = pd.Timestamp(date+'T09:30:00') In [12]: end = pd.Timestamp(date+'T16:00:00') In [13]: pd.date_range(start, end, freq='S') Out[13]: <class 'pandas.tseries.index.DatetimeIndex'> [2011-01-10 09:30:00, ..., 2011-01-10 16:00:00] Length: 23401, Freq: S, Timezone: None
Note: To see it’s a timezone, you’re in UTC-8, and 14:00 + 8:00 == 00:00 (the next day).