Pandas – How to Extract Month & Year from Datetime

how to extract month and year from datetime

This is a quick post representing code sample related to how to extract month & year from datetime column of DataFrame in Pandas.

The code sample is shown using the sample data, BrentOilPrices downloaded from this Kaggle data page.

Here is the code to load the data frame.

import pandas as pd
df = pd.read_csv('BrentOilPrices.csv')

Check the data type of the data using the following code:


The output looks like the following:

Date object
Price float64
dtype: object

Use the following command to change the date data type from object to datetime and extract the month and year.

df['Date'] = pd.to_datetime(df['Date'])
df['year'] = pd.DatetimeIndex(df['Date']).year
df['month'] = pd.DatetimeIndex(df['Date']).month

Printing data using head command would print the following:

Fig: Pandas: How to extract Month & Year from Datetime

Ajitesh Kumar
Follow me

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. For latest updates and blogs, follow us on Twitter. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking. Check out my other blog,
Posted in Data Science, Machine Learning, News. Tagged with , , .

Leave a Reply

Your email address will not be published. Required fields are marked *