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I want to firstly group different rows, if their first item in the row is the same, then flatten each columns in one group into a list.

My initial dataframe:

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And my target:

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The problem is that I cannot use simply df.groupby('key').apply(list) cause it will flatten columns val1 and val2 together`

Is there any way to do this?

over 4 years ago · Santiago Trujillo

Answer question

Answer 1 · 2022-05-16T20:55:42.981Z

Use agg instead of apply:

df.groupby('key').agg(list)

Output:

    key       val1       val2
0  key1  [1, 2, 5]  [2, 3, 6]