I'd like to add 1 if date_ > buy_date larger than 12 months else 0
example df
customer_id date_ buy_date
34555 2019-01-01 2017-02-01
24252 2019-01-01 2018-02-10
96477 2019-01-01 2017-02-18
output df
customer_id date_ buy_date buy_date>_than_12_months
34555 2019-01-01 2017-02-01 1
24252 2019-01-01 2018-02-10 0
96477 2019-01-01 2018-02-18 1
Based on what I understand, you can try adding a year to buy_date and then subtract from date_ , then check if days are + or -.
df['buy_date>_than_12_months'] = ((df['date_'] -
(df['buy_date']+pd.offsets.DateOffset(years=1)))
.dt.days.gt(0).astype(int))
print(df)
customer_id date_ buy_date buy_date>_than_12_months
0 34555 2019-01-01 2017-02-01 1
1 24252 2019-01-01 2018-02-10 0
2 96477 2019-01-01 2017-02-18 1
import pandas as pd
import numpy as np
values = {'customer_id': [34555,24252,96477],
'date_': ['2019-01-01','2019-01-01','2019-01-01'],
'buy_date': ['2017-02-01','2018-02-10','2017-02-18'],
}
df = pd.DataFrame(values, columns = ['customer_id', 'date_', 'buy_date'])
df['date_'] = pd.to_datetime(df['date_'], format='%Y-%m-%d')
df['buy_date'] = pd.to_datetime(df['buy_date'], format='%Y-%m-%d')
print(df['date_'] - df['buy_date'])
df['buy_date>_than_12_months'] = pd.Series([1 if ((df['date_'] - df['buy_date'])[i]> np.timedelta64(1, 'Y')) else 0 for i in range(3)])
print (df)
((df['date_'] - df['buy_date'])[i].days> 365 to ((df['date_'] - df['buy_date'])[i]> np.timedelta64(1, 'Y')) and thanks for logic.