Pandas – How to Extract Month & Year from Datetime

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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:

df.dtypes

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

Ajitesh Kumar

Ajitesh has been recently working in the area of AI and machine learning. Currently, his research area includes Safe & Quality AI. In addition, he is also passionate about various different technologies including programming languages such as Java/JEE, Javascript and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc.

He has also authored the book, Building Web Apps with Spring 5 and Angular.
Ajitesh Kumar

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