Merge multiple column values into one column for duplicate rows in python pandas

Question

I have a pandas data frame like this:

     Col1       Col2

 0    a        Jack     
 1    a        Jill     
 2    b        Bob     
 3    c        Cain     
 4    c        Sam     
 5    a        Adam     
 6    b        Abel  

What I want to do now is combine values in column 2 for each value in column 1, ie, output should be like this:

     Col1     Col2

0     a      Jack, Jill, Adam
1     b      Bob, Abel
2     c      Cain, Sam

How can I best approach this problem? Any advice would be helpful. Thanks in advance!

Answer 1

Use

df = df.groupby('Col1')['Col2'].apply(', '.join)

print(df)
Col1
a    Jack, Jill, Adam
b           Bob, Abel
c           Cain, Sam
Name: Col2, dtype: object

Use reset_index to get Col1 back as column instead of index

df = df.groupby('Col1')['Col2'].apply(', '.join).reset_index()

print(df)
  Col1              Col2
0    a  Jack, Jill, Adam
1    b         Bob, Abel
2    c         Cain, Sam

Answer 2

You can also try following as in other similar answer:

new_df = df.groupby('Col1', as_index=False).agg(', '.join)

Answer 3

Here is a different approach, try it out:

df.groupby("Col1").agg(lambda x: ', '.join(x.unique())).reset_index()


  Col1              Col2
0    a  Jack, Jill, Adam
1    b         Bob, Abel
2    c         Cain, Sam

Something to keep in mind. If your dataset was something like this:

  Col1  Col2
0    a  Jack
1    a  Jill
2    b   Bob
3    c  Cain
4    c   Sam
5    a  Adam
6    b  Abel
7    a  Adam
8    c   Sam

You would get the following output:

df.groupby("Col1").agg(lambda x: ', '.join(x)).reset_index()


  Col1                    Col2
0    a  Jack, Jill, Adam, Adam
1    b               Bob, Abel
2    c          Cain, Sam, Sam

So by using unique you remove duplicates in Col2. Hope that helps