Pandas Multiindex Dataframe - Selecting Max From One Index Within Multiindex

I've got a dataframe with a multi index of Year and Month like the following | |Value Year |Month| | 1 | 3 1992 | 2 | 5 | 3 | 8 | ... | ... 1993

Solution 1:

Exactly right:

df.groupby(level=0).apply(max)

In my sample DataFrame:

                     0
Caps Lower            
A    a     0  0.246490
           1 -1.265711
           2 -0.477415
           3 -0.355812
           4 -0.724521
     b     0 -0.409198
           1 -0.062552
           2 -0.731789
           3  1.131616
           4  0.085248
B    a     0  0.193948
           1  2.010710
           2  0.289300
           3  0.305373
           4  1.376965
     b     0  0.210522
           1  1.431279
           2 -0.247171
           3  0.899074
           4  0.639926

Result:

             0
Caps          
A     1.131616
B     2.010710

This is how I created the DataFrame, by the way:

df = pd.DataFrame(np.random.randn(5,4), columns = l)
df.columns = pd.MultiIndex.from_tuples(df.columns, names=['Caps','Lower'])
df = pd.DataFrame(df.unstack())

Solution 2:

Simplier solution is max only:

#bernie's sample data
df = df.max(level=0)
print (df)
             0
Caps          
A     1.131616
B     2.010710