[FIXED] Panda count totals of multiple excel columns

Issue

I have excel data that i modified to give me 1's = Filled cell 0's = Not Filled cell

Column A	Column B	Column C	Column D
1	0	1	0
1	1	1	0
0	0	1	0
0	0	1	0

what i want to get is:

	Filled	Not Filled
Column A	2	2
Column B	1	3
Column C	4	0
Column D	0	4

i tried:

summary_new = df2.groupby(['Column A','Column B','Column C','Column D'], as_index=False).agg(
    FILLED_ITEM = pd.NamedAgg(column=([['Column A','Column B','Column C','Column D']]).astype(int), aggfunc=lambda x: x.eq(1).sum()),
    NOT_FILLED_ITEM = pd.NamedAgg(column=([['Column A','Column B','Column C','Column D']]).astype(int), aggfunc=lambda x: x.eq(0).sum())).reset_index(drop=True)

Solution

Similarly to @Corralien's approach but as a single command, using sum and eval:

out = (df.sum().to_frame(name='Filled')
         .eval('Not_Filled = @df.shape[1]-Filled')
      )

Variant: .eval(...) can be replaced by .assign(**{'Not Filled': lambda d: df.shape[1]-d['Filled']}).

Output:

          Filled  Not_Filled
Column A       2           2
Column B       1           3
Column C       4           0
Column D       0           4

Answered By - mozway