All days instead of business days?

[ghost]

Hi,

I am very new to github and miss a discussion board for pandas. Not sure if issues is the right place for my question, so feel free to delete it, but please point to the right place for questions.

The question: I need to aggregate hourly time series to the daily scale, that would include all days, 7 per week. Currently i find only bday class in datetools:

daily_ts = ts.groupby(lambda x: datetools.bday(x)).aggregate(np.nansum)

But bday will skip weekends. datetools.day seem to return timeseries with the same time resolution.
How to include weekend days?

Many thanks for developing pandas, it's truly nice, and really fast, even when working with large datasets!

[ghost]

For the moment i solved the problem by copying creating a calendar days class, CDay, which is a copy of BDay, but with 7 days in the week.

But i guess i am just missing a nicer solution..

[wesm]

No need for a calendar days class for this purpose. I think you want:

from pandas.core.datetools import normalize_date
daily_ts = ts.groupby(normalize_date).aggregate(np.nansum)

# alternately
daily_ts = ts.groupby(normalize_date).aggregate(Series.sum)

I actually plan to make this work (right now it does, but not with NaNs...making a note to make the change to the code soon):

daily_ts = ts.groupby(normalize_date).sum()

For converting to calendar day frequency, ts.asfreq(datetools.day) will do

Hope this helps

[ghost]

Nice, that's what i was looking for!

Thanks a lot,
Mikhail

[ghost]

Wes,

I can't find the answer in the documentation, thus asking here again:

• How can I aggregate data by the months of the year? With 12 bins only, similar to the weekday() as in the documentation: http://pandas.sourceforge.net/groupby.html#aggregation ?