Python: datetime64 issues with range
Question: 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 under EDIT: SOLUTION of the OP question
asked [here](http://stackoverflow.com/questions/15930885/converting-
irregularly-time-stamped-measurements-into-equally-spaced-time-weigh) except
with `datetime64` format. Possible?


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).

