multi-monthly mean with pandas' Series

Question

I have a sequence of datetime objects and a series of data which spans through several years. A can create a Series object and resample it to group it by months:

df=pd.Series(varv,index=dates)
multiMmean=df.resample("M", how='mean')
print multiMmean

This, however, outputs

2005-10-31    172.4
2005-11-30     69.3
2005-12-31    187.6
2006-01-31    126.4
2006-02-28    187.0
2006-03-31    108.3
...
2014-01-31     94.6
2014-02-28     82.3
2014-03-31    130.1
2014-04-30     59.2
2014-05-31     55.6
2014-06-30      1.2

which is a list of the mean value for each month of the series. This is not what I want. I want 12 values, one for every month of the year with a mean for each month through the years. How do I get that for multiMmean?

I have tried using resample("M",how='mean') on multiMmean and list comprehensions but I cannot get it to work. What am I missing?

Thank you.

Answer 1

the following worked for me:

# create some random data with datetime index spanning 17 months
s = pd.Series(index=pd.date_range(start=dt.datetime(2014,1,1), end = dt.datetime(2015,6,1)), data = np.random.randn(517))

In [25]:
# now calc the mean for each month
s.groupby(s.index.month).mean()
Out[25]:
1     0.021974
2    -0.192685
3     0.095229
4    -0.353050
5     0.239336
6    -0.079959
7     0.022612
8    -0.254383
9     0.212334
10    0.063525
11   -0.043072
12   -0.172243
dtype: float64

So we can groupby the month attribute of the datetimeindex and call mean this will calculate the mean for all months