To group on multiple criteria, pass a list of the columns or criteria:
df['birthdate'].groupby([df.birthdate.dt.year, df.birthdate.dt.month]).agg('count')
Example:
In [165]:
df = pd.DataFrame({'birthdate':pd.date_range(start=dt.datetime(2015,12,20),end=dt.datetime(2016,3,1))})
df.groupby([df['birthdate'].dt.year, df['birthdate'].dt.month]).agg({'count'})
Out[165]:
birthdate
count
birthdate birthdate
2015 12 12
2016 1 31
2 29
3 1
UPDATE
As of version 0.23.0
the above code no longer works due to the restriction that multi-index level names must be unique, you now need to rename
the levels in order for this to work:
In[107]:
df.groupby([df['birthdate'].dt.year.rename('year'), df['birthdate'].dt.month.rename('month')]).agg({'count'})
Out[107]:
birthdate
count
year month
2015 12 12
2016 1 31
2 29
3 1
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