I have 2 columns named "deleted_at" (date the client canceled the service) and "birth_date" (of a client). I already transformed the string into date type using pd.to_datetime. Example:

mydataframe.loc[:,'deleted_at'] = pd.to_datetime(mydataframe['deleted_at']).

I am trying to calculate the age of the client using:

mydataframe [age] = (mydataframe['deleted_at'] - mydataframe['birth_date'])/365.25

The problem is this code is returning the date in days and I would like to receive in years. Example:

[deleted_at] 2018-06-17 23:59:08 - [birth_date] 1966-01-25

Is returning: 52 days 09:27:43.101984942. Should return 52 years, x months, y days, or even just 52 years. Is there an easy way to do that?

CodePudding user response：

this solution is much easier:

mydataframe[age] = (mydataframe['deleted_at'].dt.year - mydataframe['birth_date'].dt.year)

you can call day, week, month and year

CodePudding user response：

You can use relativedelta from dateutil package (already installed with pandas)

from dateutil.relativedelta import relativedelta

cols = ['deleted_at', 'birth_date']
df['relativedelta'] = df[cols].apply(lambda x: relativedelta(x[0], x[1]), axis=1)

Output:

Setup:

import pandas as pd

df = pd.DataFrame({'deleted_at': [pd.Timestamp('2018-06-17 23:59:08')],
                   'birth_date': [pd.Timestamp('1966-01-25')]})