copy values in a dataframe according to specific filter-CodePudding

I have this dataframe:

time	open	close	giorno	ora
2021-09-01 08:00:00	152.03	152.31	1	8
2021-09-01 09:00:00	152.21	152.28	1	9
2021-09-01 10:00:00	152.27	153.89	1	10
2021-09-01 11:00:00	153.9	154.31	1	11
2021-09-01 12:00:00	154.32	154.28	1	12
2021-09-01 13:00:00	154.28	153.44	1	13
2021-09-02 08:00:00	152.98	153.27	2	8
2021-09-02 09:00:00	153.27	153.56	2	9
2021-09-02 10:00:00	153.54	153.94	2	10
2021-09-02 11:00:00	153.94	153.83	2	11
2021-09-02 12:00:00	153.84	153.36	2	12
2021-09-02 13:00:00	153.36	153.08	2	13
2021-09-03 08:00:00	153.67	153.96	3	8
2021-09-03 09:00:00	153.68	153.92	3	9
2021-09-03 10:00:00	153.96	154.11	3	10
2021-09-03 11:00:00	154.11	153.67	3	11
2021-09-03 12:00:00	153.66	153.76	3	12
2021-09-03 13:00:00	153.77	153.63	3	13
2021-09-07 08:00:00	154.07	154.46	7	8
2021-09-07 09:00:00	154.38	154.72	7	9
2021-09-07 10:00:00	154.72	155.49	7	10
2021-09-07 11:00:00	155.47	155.8	7	11
2021-09-07 12:00:00	155.79	155.59	7	12
2021-09-07 13:00:00	155.58	156.87	7	13

I want to copy the value in this way:

if  "ora"=10 then copy "open" cell in all the rows in the same day (column "giorno") in a new column

For exemple about the time 2021-09-01 10:00:00 i want to copy the value 152.27 and past to a new column corrisponding to the rows of giorno=1

time	open	close	giorno	ora	newColumn
2021-09-01 08:00:00	152.03	152.31	1	8	152.27
2021-09-01 09:00:00	152.21	152.28	1	9	152.27
2021-09-01 10:00:00	152.27	153.89	1	10	152.27
2021-09-01 11:00:00	153.9	154.31	1	11	152.27
2021-09-01 12:00:00	154.32	154.28	1	12	152.27
2021-09-01 13:00:00	154.28	153.44	1	13	152.27

CodePudding user response：

You can use apply with a lambda function to achieve this.

df['newColumn'] = df.apply(lambda x: float(df['open'][(df['giorno'] == x['giorno']) & (df['ora'] == 10)]), axis=1)

full code:

import pandas as pd

df = pd.read_html('https://stackoverflow.com/questions/70914561/copy-values-in-a-dataframe-according-to-specific-filter')[0]
df['newColumn'] = df.apply(lambda x: float(df['open'][(df['giorno'] == x['giorno']) & (df['ora'] == 10)]), axis=1)
df[df['giorno'] == 1]

output:

    time                open    close   giorno  ora newColumn
0   2021-09-01 08:00:00 152.03  152.31  1       8   152.27
1   2021-09-01 09:00:00 152.21  152.28  1       9   152.27
2   2021-09-01 10:00:00 152.27  153.89  1       10  152.27
3   2021-09-01 11:00:00 153.90  154.31  1       11  152.27
4   2021-09-01 12:00:00 154.32  154.28  1       12  152.27
5   2021-09-01 13:00:00 154.28  153.44  1       13  152.27