Pandas multiindex dataframe - Selecting max from o

问题:

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 |  1  |  2
     | ... | ...

I'm trying to select the maximum Value for each year and put that in a DF like this:

     | Max
Year |  
1992 |  5
1993 |  2
     | ... 

There's not much info on multi-indexes, should I simply do a group by and apply or something similar to make it more simple?

回答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())

回答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