Sentry Answers>Python>

Select multiple columns in Python Pandas

Select multiple columns in Python Pandas

David Y.

The ProblemJump To Solution

How do I select multiple columns from an existing DataFrame and create a new DataFrame with them?

The Solution

We can do this by creating a list of the column names we want and passing them to the DataFrame constructor method, along with the original DataFrame. The code below shows an example:

Click to Copy
import pandas # Our main DataFrame main = pandas.DataFrame([["apple", 1, 2], ["orange", 3, 4], ["pear", 5, 6]], columns=["product", "cost_price", "sale_price"]) print(main) print("\n") # Our smaller DataFrame subset = pandas.DataFrame(main, columns=["product", "sale_price"]) print(subset)

This code will produce the following output:

Click to Copy
product cost_price sale_price 0 apple 1 2 1 orange 3 4 2 pear 5 6 product sale_price 0 apple 2 1 orange 4 2 pear 6
  • Sentry BlogPython Performance Testing: A Comprehensive Guide
  • Sentry BlogLogging in Python: A Developer’s Guide
  • logo
    Listen to the Syntax Podcast

    Tasty treats for web developers brought to you by Sentry. Get tips and tricks from Wes Bos and Scott Tolinski.


Loved by over 4 million developers and more than 100,000 organizations worldwide, Sentry provides code-level observability to many of the world’s best-known companies like Disney, Peloton, Cloudflare, Eventbrite, Slack, Supercell, and Rockstar Games. Each month we process billions of exceptions from the most popular products on the internet.

© 2024 • Sentry is a registered Trademark
of Functional Software, Inc.