Subtract an year from a datetime column in pandas

Question

I have a datetime column as below -

>>> df[\'ACC_DATE\'].head(2)
538   2006-04-07
550   2006-04-12
Name: ACC_DATE, dtype: datetime64[ns]


        

Answer 1

You can use DateOffset to achieve this:

In[88]:
df['NEW_DATE'] = df['ACC_DATE'] - pd.DateOffset(years=1)
df

Out[88]: 
        ACC_DATE   NEW_DATE
index                      
538   2006-04-07 2005-04-07
550   2006-04-12 2005-04-12

Answer 2

You could use pd.Timedelta:

df["NEW_DATE"] = df["ACC_DATE"] - pd.Timedelta(days=365) 

Or replace:

df["NEW_DATE"] = df["ACC_DATE"].apply(lambda x: x.replace(year=x.year - 1))

But neither will catch leap years so you could use dateutil.relativedelta :

from dateutil.relativedelta import  relativedelta

df["NEW_DATE"] = df["ACC_DATE"].apply(lambda x: x - relativedelta(years=1))

Answer 3

Use DateOffset:

df["NEW_DATE"] = df["ACC_DATE"] - pd.offsets.DateOffset(years=1)
print (df)
        ACC_DATE   NEW_DATE
index                      
538   2006-04-07 2005-04-07
550   2006-04-12 2005-04-12