Fill the NA value in one column according to values of similar columns [duplicate]

Answer 1

try sort_values first to make Nan in last and then use group by with ffill()

df.sort_values(by=['C'],inplace=True)
df = df.groupby(['A','B']).ffill()

    A   B   C
0   aa  xx  2
1   bb  yy  3
2   cc  zz  8
3   aa  xx  2

Answer 2

Use GroupBy.ffill with DataFrame.sort_values and DataFrame.sort_index for NaNs to end of groups:

df['C'] = df.sort_values(['A','B','C']).groupby(['A','B'])['C'].ffill().sort_index()
print (df)
    A   B  C
0  aa  xx  2
1  bb  yy  3
2  cc  zz  8
3  aa  xx  2

Another solution with forward and back filling per groups:

df['C'] = df.groupby(['A','B'])['C'].apply(lambda x: x.ffill().bfill())