Add a new column to a DataFrame in Python Pandas
David Y.
—The Problem
How do I add a new column to an existing Pandas DataFrame? The new column should have the same number of rows as existing columns.
The Solution
We can do this using the DataFrame.assign method. When called on a given DataFrame, this method creates a copy of that DataFrame with one or more additional columns added.
The new columns can contain manually specified values, or values can be computed for each row based on other columns. Look at the following example code:
import pandas # Create a dataframe with products and their cost prices products = pandas.DataFrame([["apple", 2.0], ["orange", 3.0], ["pear", 4.0]], columns=["product", "cost_price"]) print(products) # Add a stock count column with manual data products = products.assign(stock_count=[50, 40, 30]) print(products) # Add a sale price column that calculates a 50% markup products = products.assign(sale_price=lambda row: row.cost_price * 1.5) print(products)
This code will print the products DataFrame with two, three and then four columns. Note the use of a lambda expression in the creation of the sale_price column – the values for this column are created by running the function on each row.
- Sentry BlogPython Performance Testing: A Comprehensive Guide
- Syntax.fmListen to the Syntax Podcast
- Sentry BlogLogging in Python: A Developer’s Guide
- CodecovPython - Codecov
- Listen to the Syntax Podcast
![Syntax.fm logo]()
Tasty treats for web developers brought to you by Sentry. Get tips and tricks from Wes Bos and Scott Tolinski.
SEE EPISODES
Considered “not bad” by 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.