How to extract month and year separately from datetime in pandas?

Learn how to extract month and year separately from datetime in pandas? By Pranit Sharma Last updated : September 19, 2023

The datetime is a library in Python which is a collection of date and time. Inside Datetime, we can access date and time in any format, but usually date is present in the format of "yy-mm-dd" and time is present in the format of "HH:MM:SS".

Here,

yy means year
mm means month
dd means day
HH means hours
MM means minutes
SS means seconds

Problem statement

While accessing the date and time from datetime, we always get date and time together, here we are going to learn how to extract month and year separately DateTime?

Extracting month and year separately from datetime in pandas

For this purpose, we will use the .dt.month property to extract the month part and the .dt.date property to extract the date part from the pandas column. You need to use the pd.to_datetime() method by specifying the column name.

Let us understand with the help of an example:

Python program to extract month and year separately from datetime in pandas

# Importing datetime package
import pandas as pd

# Importing datetime package
import datetime

# Creating a dictionaries of datetime
d = {'Datetime':['2021-01-01 20:04:31',
                '2022-07-01 16:14:11',
                '2023-03-01 19:13:22',
                '2024-08-01 23:22:17',
                '2025-12-01 2:54:49']}

# Creating a DataFrame
df = pd.DataFrame(d)

# Display original DataFrame
print("Original DataFrame:\n",df,"\n")

# Extracting month and year from Datetime
# Adding a new column named Month & year 
# having months and years only
df['Month'] = pd.to_datetime(df['Datetime']).dt.month

df['Year'] = pd.to_datetime(df['Datetime']).dt.year

# Display modified DataFrame
print("Modified DataFrame:\n",df)