Concatenating column values into row values in Pandas

Question

I have a dataframe like the below- both columns are strings, with the ValCol being a string of comma separated integers. The index is a generic integer index with no meaning.

NameCol    ValCol
Name1      555, 333
Name2      433
Name1      999
Name3      123
Name2      533

What's the best way to aggregate it to

NameCol    ValCol
Name1      555, 333, 999
Name2      433, 533
Name3      123

T don't care about the order of the comma separated integers, but I do need to keep commas between them. It likely will be a very small dataframe, <100 records, so efficiency isn't critical.

I feel like there should be some groupby approach to this, but I haven't figured it out yet.

root · Accepted Answer · 2016-09-01 17:04:16Z

4

Using a groupby approach:

df = df.groupby('NameCol')['ValCol'].apply(', '.join).reset_index()

The resulting output:

  NameCol         ValCol
0   Name1  555, 333, 999
1   Name2       433, 533
2   Name3            123

answered Sep 1, 2016 at 17:04

root

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1 Comment

John Over a year ago

That makes so much sense and is very clean, thank you!

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