Python Pandas. Date object split by separate columns.

Question

I have dates in Python (pandas) written as \"1/31/2010\". To apply linear regression I want to have 3 separate variables: number of day, number of month, number of year.

Answer 1

This answers only your first question

One solution is to extract attributes of pd.Timestamp objects using operator.attrgetter.

The benefit of this method is you can easily expand / change the attributes you require. In addition, the logic is not specific to object type.

from operator import attrgetter
import pandas as pd

df = pd.DataFrame({'date': ['1/21/2010', '5/5/2015', '4/30/2018']})

df['date'] = pd.to_datetime(df['date'], format='%m/%d/%Y')

attr_list = ['day', 'month', 'year']
attrs = attrgetter(*attr_list)
df[attr_list] = df['date'].apply(attrs).apply(pd.Series)

print(df)

        date  day  month  year
0 2010-01-21   21      1  2010
1 2015-05-05    5      5  2015
2 2018-04-30   30      4  2018