Comments (4)
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..
from pandas.
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
from pandas.
Nice, that's what i was looking for!
Thanks a lot,
Mikhail
from pandas.
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 ?
from pandas.
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from pandas.