Add days to a Date and Subtract dates in Python

Introduction¶

In this blog we will look at the following:

• Add days to a date string
• Subtract two dates

In [1]:

import pandas as pd
import numpy as np
import datetime
from datetime import timedelta
from datetime import date

Step 1:Create dummy dates¶

In [2]:

date_val = pd.Series(['22/09/2020','25-09-2020','20200927','2020-09-22T13:25'])
date_val

Out[2]:

0          22/09/2020
1          25-09-2020
2            20200927
3    2020-09-22T13:25
dtype: object

Step 2:Convert into date format¶

In [3]:

date_val_converted=pd.to_datetime(date_val)
date_val_converted

Out[3]:

0   2020-09-22 00:00:00
1   2020-09-25 00:00:00
2   2020-09-27 00:00:00
3   2020-09-22 13:25:00
dtype: datetime64[ns]

We can see that the data type of 'date_val_converted' is date time¶

Step 3:Lets add 15 days to each date¶

In [4]:

date_val_converted + timedelta(days=3)

Out[4]:

0   2020-09-25 00:00:00
1   2020-09-28 00:00:00
2   2020-09-30 00:00:00
3   2020-09-25 13:25:00
dtype: datetime64[ns]

Step 4: Subtract two dates¶

Lets subtract these dates from today's date¶

In [32]:

diff_days=[(pd.to_datetime(date.today())-i).days for i in date_val_converted]
diff_days

Out[32]:

[566, 563, 561, 565]

In [35]:

date_df=pd.DataFrame(date_val_converted)
date_df['Today'] = date.today()
date_df.columns=[['Dummy_Date','Today']]
date_df['Diff_Days']=diff_days
date_df

Out[35]:

	Dummy_Date	Today	Diff_Days
0	2020-09-22 00:00:00	2022-04-11	566
1	2020-09-25 00:00:00	2022-04-11	563
2	2020-09-27 00:00:00	2022-04-11	561
3	2020-09-22 13:25:00	2022-04-11	565

Step 5: Subtract two dates column in Pandas data frame¶

In [51]:

interim_df=pd.DataFrame(date_val_converted)
interim_df['Today']=date.today()
interim_df.columns=['Reference Date','Today']
interim_df

Out[51]:

	Reference Date	Today
0	2020-09-22 00:00:00	2022-04-23
1	2020-09-25 00:00:00	2022-04-23
2	2020-09-27 00:00:00	2022-04-23
3	2020-09-22 13:25:00	2022-04-23

In [52]:

Diff_Days= pd.to_datetime(interim_df['Today']) - pd.to_datetime(interim_df['Reference Date'])
interim_df['Diff_Days'] = Diff_Days
interim_df

Out[52]:

	Reference Date	Today	Diff_Days
0	2020-09-22 00:00:00	2022-04-23	578 days 00:00:00
1	2020-09-25 00:00:00	2022-04-23	575 days 00:00:00
2	2020-09-27 00:00:00	2022-04-23	573 days 00:00:00
3	2020-09-22 13:25:00	2022-04-23	577 days 10:35:00

Converting days(date time) into integer¶

In [53]:

interim_df['Diff_Days2']=interim_df['Diff_Days'].apply(lambda x: x.days)
interim_df

Out[53]:

	Reference Date	Today	Diff_Days	Diff_Days2
0	2020-09-22 00:00:00	2022-04-23	578 days 00:00:00	578
1	2020-09-25 00:00:00	2022-04-23	575 days 00:00:00	575
2	2020-09-27 00:00:00	2022-04-23	573 days 00:00:00	573
3	2020-09-22 13:25:00	2022-04-23	577 days 10:35:00	577

In [54]:

interim_df2 = interim_df.drop(['Diff_Days'],axis=1)
interim_df2

Out[54]:

	Reference Date	Today	Diff_Days2
0	2020-09-22 00:00:00	2022-04-23	578
1	2020-09-25 00:00:00	2022-04-23	575
2	2020-09-27 00:00:00	2022-04-23	573
3	2020-09-22 13:25:00	2022-04-23	577

In [55]:

new_nm = {'Diff_Days2': 'Diff_Days'}
interim_df2.rename(columns=new_nm,inplace=True)
interim_df2

Out[55]:

	Reference Date	Today	Diff_Days
0	2020-09-22 00:00:00	2022-04-23	578
1	2020-09-25 00:00:00	2022-04-23	575
2	2020-09-27 00:00:00	2022-04-23	573
3	2020-09-22 13:25:00	2022-04-23	577