Groupby class and count missing values in features

Question

I have a problem and I cannot find any solution in the web or documentation, even if I think that it is very trivial.

What do I want to do?

I have a datafram

Answer 1

Using the diff between count and size

g=df.groupby('CLASS')

-g.count().sub(g.size(),0)

          FEATURE1  FEATURE2  FEATURE3
CLASS                              
B             0         0         0
X             1         1         2

And we can transform this question to the more generic question how to count how many NaN in dataframe with for loop

pd.DataFrame({x: y.isna().sum()for x , y in g }).T.drop('CLASS',1)
Out[468]: 
   FEATURE1  FEATURE2  FEATURE3
B         0         0         0
X         1         1         2