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I saw this page, How to group dataframe rows into list in pandas groupby but, that's not what I need.

Let my datatable example see please.

index column1 column2
0 apple red
1 banana a
1 banana b
2 grape wow
2 grape that's
2 grape great
2 grape fruits!
3 melon oh
3 melon no
...a lot of data... ...a lot of data... ... a lot of data...

and I want to groupby ONLY index 2~3 (I need to range because my real data is hudge.)

so I want to this table

. column1 column2
0 apple red
1 banana a
1 banana b
2 grape wow that's great grape fruits!
3 melon oh no
...a lot of data... ...a lot of data... ... a lot of data...

How can I get this?

now
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1 Answers1

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Let's filter the dataframe based on index column, then groupby on the filtered dataframe.

m = df['index'].isin([2,3])

out = (pd.concat([df[~m],
                  (df[m].groupby('column1', as_index=False)
                   .agg({'index': 'first', 'column2': ' '.join}))], ignore_index=True)
       .sort_values('index', ignore_index=True))

print(out)

   index column1                   column2
0      0   apple                       red
1      1  banana                         a
2      1  banana                         b
3      2   grape  wow that's great fruits!
4      3   melon                     oh no
Ynjxsjmh
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  • omg.. Thank you so much!!! and I have a question one more, How I can get this result if 'index'is not column, and real index? If you busy you can pass this question . thank you! – now Nov 17 '22 at 06:29
  • @now You can use `df.reset_index()` first. – Ynjxsjmh Nov 17 '22 at 06:43