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I have a pandas DataFrame.

date data meter_id
2023-02-13 a 1
2023-02-13 b 2
2023-02-13 c 6
2023-02-10 d 1
2023-02-08 e 1
2023-02-08 f 2
2023-02-05 g 1
2023-02-02 h 2

I want to convert it to following unique date and columns equal unique meter_id.

date 1 2 6
2023-02-13 a b c
2023-02-10 d NaN NaN
2023-02-08 e f NaN
2023-02-05 g NaN NaN
2023-02-02 NaN h NaN
Alex
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  • I'm trying df_col = pd.DataFrame(data=df['date'].unique(), columns=['date']) meters = list(df['meter_id'].unique()) df_col[[x for x in meters]] = str([y for y in df['index']]) – Alex Feb 15 '23 at 09:07
  • What you need is to pivot the df. pd.pivot_table(df, values='date', index='meter_id, columns=['data']) – Santiago Domínguez Collado Feb 15 '23 at 10:41

0 Answers0