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Not getting my head around pandas

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I've got a pandas DataFrame that looks like:


<class 'pandas.core.frame.DataFrame'>
Int64Index: 12960 entries, 0 to 12959
Data columns (total 2 columns):
date    12960  non-null values
ms      12960  non-null values
dtypes: datetime64[ns](1), float64(1)


                     date         ms
12955 2013-08-30 23:20:00  96.868491
12956 2013-08-30 23:30:00  96.857826
12957 2013-08-30 23:40:00  92.624406
12958 2013-08-30 23:50:00  85.402094
12959 2013-08-31 00:00:00  93.870912

This is samples taken every 10 minutes going back several months.  I 
want to find the mean and variance for all the points that happened at 
the same time each day.  In other words, I want to group by date.time().

I can certainly do this by pulling all the data out of the DataFrame and 
working on it as normal Python data.  But, I suspect there's some easy 
way to do this in pandas and I'm just not seeing it.

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Not getting my head around pandas Roy Smith <roy@panix.com> - 2013-08-31 21:23 -0400

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