Browse › Jupyter Data Visualization

Create a Boxplot by Using Python in JupyterLab
Part of Jupyter Data Visualization Topic: Data Science
Access
StationX Infrastructure Labs — 3 attempts per lab
🔒 Add StationX Infrastructure Labs — $149 / year · 3 attempts per lab
Already have access? Sign in.
New to this? Try a free practice lab — a scripted hacking challenge in your browser, no account needed.
What you'll do
In this lab, you will analyze and visualize data distributions by using Python in the JupyterLab development environment.
- Load the Python NumPy, Matplotlib, and pandas libraries
- Load data stored in a comma-separated values (CSV) file into a pandas DataFrame
- Review the data in the DataFrame
- Create and compare different boxplots
- Add labels, notches, and a title to a boxplot
- Change the orientation of a boxplot
Note: Once you begin the lab, you will not be able to pause, save, or exit and then return to your lab. Please ensure that you have set aside enough time to complete the lab before you start.
- ⏱ About 30 minutes