CODEWITHSUNDEEP
pythondatetimepandas
GPB
GPB

Reputation: 2495

Python Parsing Month, year from datetime64[ns]

I have a pandas datetime object, df['issue_date'] and I would like to create an object which contains only the month and year of the object, with a '0' in front of all months with single digits. All years are > 2000 I've tried: 

[In]
import datetime

df['issue_year'] =  pd.DatetimeIndex(lcd['issue_date']).year.astype(int)
df['issue_month'] = pd.DatetimeIndex(lcd['issue_date']).month.astype(int)
df['issue_MMYY'] = df['issue_month']*1000+df['issue_year'] % 2000

But this feels (very) kludgy and slow, and also does not pad the 0 in front. In general, date time objects give me fits....can anyone help with something more elegant?

Upvotes: 0

Views: 462

Answers (1)

Brian Pendleton
Brian Pendleton

Reputation: 829

lcd = pd.DataFrame({'issue_date': pd.date_range('2015-09-01', periods=4, freq='Q')})
lcd.issue_date.apply(lambda x: x.strftime('%m%Y'))

The result:

0    092015
1    122015
2    032016
3    062016

Upvotes: 1

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