How can I identify date columns and format it to YYYY-MM-DD in Python using pandas?

Question

I am trying to format the dates in Python using Pandas. Basically, I want to identify all the date columns and convert it to YYYY-MM-DD format, overwrite and save it.

Input:

ID	NPC_code	Date1	Date2	Date3	Date4
1	10001	10-01-2020	11012019	27-Jan-18	27Jan2016
2	10002	11-01-2020	11012020	28-Jan-18	27Jan2017
3	10003	12-01-2020	11012021	29-Jan-18	27Jan2018
4	10004	13-01-2020	11012022	30-Jan-18	27Jan2019
5	10005	14-01-2020	11012023	31-Jan-18	27Jan2020

question from:https://stackoverflow.com/questions/65867773/how-can-i-identify-date-columns-and-format-it-to-yyyy-mm-dd-in-python-using-pand

Answer 1

If your column is a string, you will need to first use `pd.to_datetime',

df['Date'] = pd.to_datetime(df['Date'])

Then, use .dt datetime accessor with strftime:

df = pd.DataFrame({'Date':pd.date_range('2017-01-01', periods = 60, freq='D')})

df.Date.dt.strftime('%Y-%m-%d').astype(int)

Or use lambda function:

df.Date.apply(lambda x: x.strftime('%Y-%m-%d')).astype(int)