简体   繁体   中英

Pandas: increment datetime

I need to do some actions with date in df column

buys['date_min'] = (buys['date'] - MonthDelta(1))
buys['date_min'] = (buys['date'] + timedelta(days=5))

But it return

TypeError: incompatible type [object] for a datetime/timedelta operation

How can I do it to column?

I think you need first convert column date to_datetime , because type od values in column date is string :

buys['date_min'] = (pd.to_datetime(buys['date']) - MonthDelta(1))
buys['date_min'] = (pd.to_datetime(buys['date']) + timedelta(days=5))

EDIT:

You need parameter format to to_datetime and then another solution is with to_timedelta

buys = pd.DataFrame({'date':['01.01.2016','20.02.2016']})
print (buys)
         date
0  01.01.2016
1  20.02.2016

buys['date']= pd.to_datetime(buys['date'],format='%d.%m.%Y') 
buys['date_min'] = buys['date'] + pd.to_timedelta(5,unit='d')
print (buys)
        date   date_min
0 2016-01-01 2016-01-06
1 2016-02-20 2016-02-25

The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.

 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM