Hierarhical Multi-index counts in Pandas

Question

Say I have a multi-index dataframe in Pandas, e.g:

                         A         B         C X      Y     Z                                 bar   one    a   -0.007381 -0.365315 -0.024817              b   -1.219794  0.370955 -0.795125 baz   three  a    0.145578  1.428502 -0.408384              b   -0.249321 -0.292967 -1.849202       two    a   -0.249321 -0.292967 -1.849202       four   a    0.211234 -0.967123  1.202234 foo   one    b   -1.046479 -1.250595  0.781722              a    1.314373  0.333150  0.133331 qux   one    c    0.716789  0.616471 -0.298493       two    b    0.385795 -0.915417 -1.367644 

How can I count how many levels are contained within another level? (e.g. level Y within X)

E.g. in the case above the answer would be:

X    Y  bar  1 baz  3 foo  1 qux  2 

Update

When I try df.groupby(level=[0, 1]).count()[0] I get:

            C  D  E A    B              bar  one    1  1  1      three  1  1  1 flux six    1  1  1      three  1  1  1 foo  five   1  1  1      one    1  1  1      two    2  2  2 

Answer 1

You can do the following (group by level X and then calculate the number of unique values of Y in each group, which is easier when the index is reset):

In [15]: df.reset_index().groupby('X')['Y'].nunique() Out[15]:  X bar    1 baz    3 foo    1 qux    2 Name: Y, dtype: int64