Pandas replace with value from another row

Question

I have a table:

Object	Col1	Col2	Col3	Col4
reference	10	14	7	29
Obj1	0	9	1	30
Obj2	1	16	0	17
Obj3	9	21	3	0
Obj4	11	0	4	22

I want to transform it by condition: if any cell (except the cells of the 1st row) is =0, then it must be replaced with an incremented (X+1) value from the 1st row of this column.

The resulting table is:

Object	Col1	Col2	Col3	Col4
reference	10	14	7	29
Obj1	11	9	1	30
Obj2	1	16	8	17
Obj3	9	21	3	30
Obj4	11	15	4	22

I've tried this variant:

df = np.where(df[df == 0] == 0, df.iloc[0] + 1, df)

but the result is ndarray, not DataFrame and the performance is not well enough.

Is there a way to do this using only pandas' utils?

Answer 1

Use DataFrame.mask:

out = df.mask(df == 0, df.iloc[0] + 1, axis=1)
print (out)
           Col1  Col2  Col3  Col4
Object                           
reference    10    14     7    29
Obj1         11     9     1    30
Obj2          1    16     8    17
Obj3          9    21     3    30
Obj4         11    15     4    22