1. Read in the college dataset, and find a few basic summary statistics on the undergraduate population and SAT math scores by institution and religious affiliation:

>>> college = pd.read_csv('data/college.csv')
>>> cg = college.groupby(['STABBR', 'RELAFFIL']) 
                ['UGDS', 'SATMTMID'] 
                .agg(['size', 'min', 'max']).head(6)

2. Notice that both index levels have names and are the old column names. The column levels, on the other hand, do not have names. Use the rename_axis method to supply level names to them:

>>> cg = cg.rename_axis(['AGG_COLS', 'AGG_FUNCS'], axis='columns')
>>> cg

3. Now that each axis level has a name, reshaping is a breeze. Use the stack method to move the AGG_FUNCS column to an index level:

>>> cg.stack('AGG_FUNCS').head()

4. By default, stacking places the new column level in the innermost position. Use the swaplevel method to switch the placement of the levels:

>>> cg.stack('AGG_FUNCS').swaplevel('AGG_FUNCS', 'STABBR',
                                    axis='index').head()

5. We can continue to make use of the axis level names by sorting levels with the sort_index method:

>>> cg.stack('AGG_FUNCS') 
      .swaplevel('AGG_FUNCS', 'STABBR', axis='index') 
      .sort_index(level='RELAFFIL', axis='index') 
      .sort_index(level='AGG_COLS', axis='columns').head(6)

6. To completely reshape your data, you might need to stack some columns while unstacking others. Chain the two methods together in a single command:

>>> cg.stack('AGG_FUNCS').unstack(['RELAFFIL', 'STABBR'])

7. Stack all the columns at once to return a Series:

>>> cg.stack(['AGG_FUNCS', 'AGG_COLS']).head(12)
STABBR  RELAFFIL  AGG_FUNCS  AGG_COLS
AK      0         count      UGDS            7.0
                             SATMTMID        0.0
                  min        UGDS          109.0
                  max        UGDS        12865.0
        1         count      UGDS            3.0
                             SATMTMID        1.0
                  min        UGDS           27.0
                             SATMTMID      503.0
                  max        UGDS          275.0
                             SATMTMID      503.0
AL      0         count      UGDS           71.0
                             SATMTMID       13.0
dtype: float64