Hi everyone,

[0kingkhan05633-maker]

Hi everyone,

I've been using the VS Code Jupyter extension to work on some large datasets, but I've noticed significant slowdowns and lag when running cells, especially those that involve heavy computations or large DataFrame manipulations.

• Has anyone experienced similar performance issues?
• Are there recommended settings or best practices to optimize Jupyter Notebook performance in VS Code?
• Would using a different Python environment or hardware setup help?

Any advice or tips would be greatly appreciated!

Thanks in advance!

Originally posted by @arjunresha in microsoft/vscode-jupyter#16898

[MuqeetVohra]

Hi! I’ve run into similar slow performance in the VS Code Jupyter environment, especially when working with large DataFrames. A few things that helped significantly:

1. Disable Notebook IntelliSense

VS Code tries to analyze the entire notebook, which slows down editing and execution.

Settings → Notebook: IntelliSense → Disable

2. Limit the Variable Explorer

The explorer can freeze when it tries to inspect large DataFrames. Adjusting these helps:

• Jupyter: Variable Explorer Exclude Large Variables
• Jupyter: Variable Explorer Max Output Size

3. Disable automatic plot rendering

Large plots can cause UI lag.

Jupyter › Plot Viewer: Receiver Enabled → Off

4. Run Jupyter outside of VS Code

Heavy workloads run more smoothly in a browser-based interface such as JupyterLab.

5. Use a clean Python environment

A fresh lightweight environment often improves performance:

python -m venv venv
venv\Scripts\activate
pip install numpy pandas jupyter ipykernel

6. Avoid displaying very large DataFrames

Showing huge outputs can freeze the interface. Prefer:
df.head()
df.info()

These adjustments removed most of the lag for me. Hopefully they help!

[creativeopey04-bit]

Hi