I have dataframe like below
A,B,C,D
91102,1,john,
91102,2,john,
91102,3,john,
91102,1,,mary
91102,2,,mary
91102,3,,mary
91103,1,sarah,
91103,2,sarah,
91103,3,sarah,
91103,1,,khan
91103,2,,khan
91103,3,,khan
and I want groupby column A and column B and want get desired output like below
A,B,C,D
91102,1,john,mary
91102,2,john,mary
91102,3,john,mary
91103,1,sarah,khan
91103,2,sarah,khan
91103,3,sarah,khan
I tried below but not giving desired output
df=df.groupby(['A', 'B'], as_index=False).agg('' .join)
CodePudding user response:
In the groupby
you could back-fill and then take the first row of the group.
df.groupby(['A','B'], as_index=False).apply(lambda x: x.bfill().iloc[0])
Result
A B C D
0 91102 1 john mary
1 91102 2 john mary
2 91102 3 john mary
3 91103 1 sarah khan
4 91103 2 sarah khan
5 91103 3 sarah khan
CodePudding user response:
Try:
x = df.set_index(["A", "B"]).stack().unstack().reset_index()
print(x)
Prints:
A B C D
0 91102 1 john mary
1 91102 2 john mary
2 91102 3 john mary
3 91103 1 sarah khan
4 91103 2 sarah khan
5 91103 3 sarah khan