calculate datetime-difference in years, months, etc. in a new pandas dataframe column

Question

I have a pandas dataframe looking like this:

Name    start        end
A       2000-01-10   1970-04-29

I want to add a new column providing the

Answer 1

Similar to @DeepSpace's answer, here's a SAS-like implementation:

import pandas as pd
from dateutil import relativedelta

def intck_month( start, end ):
    rd = relativedelta.relativedelta( pd.to_datetime( end ), pd.to_datetime( start ) )
    return rd.years, rd.months

Usage:

>> years, months = intck_month('1960-01-01', '1970-03-01')
>> print(years)
10
>> print(months)
2