Add Months to datetime Object in Python

In this article, let’s delve into the techniques for Add Months to datetime Object in Python. Working with dates and times often requires manipulation and adjustment, and understanding how to add months to a datetime object is a crucial skill. We will explore various methods and libraries to achieve this task, providing you with a comprehensive guide on enhancing the flexibility of datetime objects in Python. 

Add Months to datetime Object in Python

In Python, there are various methods to Add Months to datetime Object in Python. In this discussion, we will explore some commonly used techniques along with illustrative examples.

• Using NumPy Library
• Using relativedelta
• Using Panda’s Library
• By Creating new Function

Add Months to datetime using NumPy Library

In this example we use the NumPy library, to create a datetime object using the np.datetime64() method and then add months using timedelta using the np.timedelta64() method. A string of date format is passed in the np.datetime64() method and the required number of months is added using the np.timedelta64() method.

Python3

# import packages
import numpy as np

# adding months to a given date
print('old date is : ' + str(np.datetime64('2022-04')))
new_date = np.datetime64('2022-04') + np.timedelta64(5, 'M')
print('new date is : '+str(new_date))

Output:

old date is : 2022-04
new date is : 2022-09

Add Months to datetime using relativedelta

In this example, we use datetime and dateutil packages. The current date is known by using the datetime.date() method is used to create a date object by specifying the year, month, and day, and by using the relativedelta() method we add the number of months, and finally, we get a new datetime object.

Python3

# import packages
from datetime import date
from dateutil.relativedelta import relativedelta

# adding months to a particular date
print('date : ' + str(date(2020, 5, 15)))
new_date = date(2020, 5, 15) + relativedelta(months=5)
print('new date is : '+str(new_date))

Output:

date : 2020-05-15
new date is : 2020-10-15

Add Months to datetime using Panda’s Library.

In this example, we import the pandas’ package. In pandas, a string is converted to a datetime object using the pd.to_datetime() method and pd.DateOffset() method is used to add months to the created pandas object. finally, a new datetime object is created.

Python3

# import packages
import pandas as pd

# adding months to a particular date
present = '2022-05-05'
print('date : ' + present)
new_date = pd.to_datetime(present)+pd.DateOffset(months=5)
print('new date is : '+str(new_date))

Output:

date : 2022-05-05 new 
date is : 2022-10-05 00:00:00

Add Months to datetime by Creating New Function

In this example, the add_months function takes a datetime object and the number of months to add. It then calculates the new year and month values and creates a new datetime object with these updated values. Finally, it prints the original and new dates for verification.

Python3

from datetime import datetime, timedelta

def add_months(current_date, months_to_add):
    new_date = datetime(current_date.year + (current_date.month + months_to_add - 1) // 12,
                        (current_date.month + months_to_add - 1) % 12 + 1,
                        current_date.day, current_date.hour, current_date.minute, current_date.second)
    return new_date

# Example usage
current_date = datetime(2023, 1, 15, 12, 30, 45)
months_to_add = 3

new_date = add_months(current_date, months_to_add)

print(f"date is : {current_date}")
print(f"date is : {new_date}")

Output:

date is : 2023-01-15 12:30:45 
date is : 2023-04-15 12:30:45