Subset Pandas Dataframe Based On Annual Returning Period Covering Multiple Months

This question is similar to Selecting Pandas DataFrame records for many years based on month & day range, but both the question and answer doesn't seem to cover my case import

Solution 1:

I would create a column of (month, day) tuples:

month_day = pd.concat([
                df.index.to_series().dt.month, 
                df.index.to_series().dt.day
            ], axis=1).apply(tuple, axis=1)

You can then compare them directly:

df[(month_day >= (startMM, startdd)) & (month_day <= (endMM, enddd))]

Solution 2:

Alternative solution:

In [79]: x = df.assign(x=df.index.strftime('%m-%d')) \
               .query("'02-15' <= x <= '10-03'").drop('x',1)

In [80]: x
Out[80]:
                   A
2010-02-15 -1.0046632010-02-160.6833522010-02-170.1585182010-02-18 -0.4474142010-02-190.078998
...              ...
2012-09-221.3782532012-09-231.2158852012-09-240.2030962012-09-25 -1.6669742012-09-260.231987

[687 rows x 1 columns]

In [81]: x.index.month.unique()
Out[81]: Int64Index([2, 3, 4, 5, 6, 7, 8, 9, 10], dtype='int64')