grouper_example2.py

freq='M'
# or 'D' or 'Y'
df = df[['dates', 'types']].groupby([pd.Grouper(key='dates', freq=freq)]).agg('count').reset_index()

"""
       dates  count
2 2012-07-31      0
1 2012-06-30      1
3 2012-08-31      1
0 2012-05-31      2
"""

# group by the category being counted, or count in this case
group = df.groupby('count')
print(group)
"""
<pandas.core.groupby.generic.DataFrameGroupBy object at 0x7fc04f3b9cd0>
"""