How add value in second row into first row?

I would like to add a new columns from a values of ‘Pr’ in second rows for each value same id and date.

Input a:

ID	Date order	Date restock	Pr	Infos
778005	2022-04-07 11:34:46.0	NaN	87.0;113001.0;00	a
778005	2022-04-07 11:34:46.0	NaN	87.0;113159.0;FC	at
7001	2021-12-10 13:50:46.0	2021-12-13 00:00:00.0	87.0;271007.0;BV	b
7001	2021-12-10 13:50:46.0	2021-12-13 00:00:00.0	87.0;286005.0;BV	bt
778005	2022-05-24 12:22:56.0	NaN	87.0;113001.0;00	cc
778005	2022-05-24 12:22:56.0	NaN	87.0;113159.0;FC	cct
778005	2022-05-23 10:49:34.0	2022-05-29 00:00:00.0	87.0;113001.0;00	d
778005	2022-05-23 10:49:34.0	2022-05-29 00:00:00.0	87.0;113159.0;FC	dt
7001	2022-01-06 08:48:01.0	2022-01-13 00:00:00.0	87.0;271007.0;BV	rr
7001	2022-01-06 08:48:01.0	2022-01-13 00:00:00.0	87.0;286005.0;BV	rrt

Output:

ID	Date order	Date restock	Pr_1	Infos	Pr_2
778005	2022-04-07 11:34:46.0	NaN	87.0;113001.0;00	a	87.0;113159.0;FC
7001	2021-12-10 13:50:46.0	2021-12-13 00:00:00.0	87.0;271007.0;BV	b	87.0;286005.0;BV
778005	2022-05-24 12:22:56.0	NaN	87.0;113001.0;00	cc	87.0;113159.0;FC
778005	2022-05-23 10:49:34.0	2022-05-29 00:00:00.0	87.0;113001.0;00	d	87.0;113159.0;FC
7001	2022-01-06 08:48:01.0	2022-01-13 00:00:00.0	87.0;271007.0;BV	rr	87.0;286005.0;BV

I wrote this code but ValueError: Index contains duplicate entries, cannot reshape

out = (a.pivot('ID', 'Date restock', 'Pr')
       .add_prefix('Pr_').fillna(0)
       .assign(type= a.groupby([['ID', 'Date order', 'Date restock']])['Pr'].first())
       .reset_index()
       .rename_axis(columns=[None]))
out

How can I fix it? Thank you.

Answer

here is one way to do it

taking cumcount to identify the duplicate rows, then concatenating the duplicate row as a column with the original df, backfilling the null values and then keeping only the first row

df['cc'] = df.groupby(['Date order']).cumcount()
df2=pd.concat([df, 
           df[df['cc'] == 1][[ 'Pr']]],  axis=1).fillna(method='bfill')
df2 = df2[df['cc'] == 0].drop(columns='cc')
df2

    ID      Date order                       Date restock   Pr               Infos  Pr
0   778005  2022-04-07 11:34:46.0   NaN                     87.0;113001.0;00    a   87.0;113159.0;FC
2   7001    2021-12-10 13:50:46.0   2021-12-13 00:00:00.0   87.0;271007.0;BV    b   87.0;286005.0;BV
4   778005  2022-05-24 12:22:56.0   NaN                     87.0;113001.0;00    cc  87.0;113159.0;FC
6   778005  2022-05-23 10:49:34.0   2022-05-29 00:00:00.0   87.0;113001.0;00    d   87.0;113159.0;FC
8   7001    2022-01-06 08:48:01.0   2022-01-13 00:00:00.0   87.0;271007.0;BV    rr  87.0;286005.0;BV