datetime reading a different format from the real value

I’m trying to reformat a datetime pattern on csv’s files:

Original date format:

DAY/MONTH/YEAR

Expected Result:

YEAR/MONTH/DAY

rows = df['clock_now'] is:

22/05/2022 12:16
22/05/2022 12:20
22/05/2022 12:21
22/05/2022 12:44
22/05/2022 12:47
22/05/2022 12:47
22/05/2022 12:51

Here is my complete code:

import pandas as pd
import datetime

filials= [
    'base.csv',
    'max.csv'
]

for filial in filials:
    df = pd.read_csv(filial)
    rows = df['clock_now']
    for row in rows:

        change_format = datetime.datetime.strptime(row, '%d/%m/%Y %H:%M')
        final_format = change_format.strftime('%Y/%m/%d %H:%M')

        df.loc[df['clock_now'] == row, 'clock_now'] = final_format
    df.to_csv(filial, index=False)

Returns this error saying format error in one of the values, but there is no '2022/05/22 12:47' value in rows = df['clock_now'].

change_format = datetime.datetime.strptime(row, '%d/%m/%Y %H:%M')
File "C:\Users\Computador\AppData\Local\Programs\Python\Python310\lib\_strptime.py", line 568, in _strptime_datetime
    tt, fraction, gmtoff_fraction = _strptime(data_string, format)
File "C:\Users\Computador\AppData\Local\Programs\Python\Python310\lib\_strptime.py", line 349, in _strptime

raise ValueError("time data %r does not match format %r" %

ValueError: time data '2022/05/22 12:47' does not match format '%d/%m/%Y %H:%M'

What am I missing out?

>Solution :

You can try this,

dt_rows = pd.to_datetime(rows)
dt_rows = pd.Series(map(lambda dt:dt.strftime("%Y/%m/%d %H:%M"), dt_rows))

Output –

0    2022/05/22 12:20
1    2022/05/22 12:21
2    2022/05/22 12:44
3    2022/05/22 12:47
4    2022/05/22 12:47
5    2022/05/22 12:51
dtype: object