Interactive Jupyter Notebook

We're excited to introduce interactive Jupyter Notebook Outputs 🚀

What are interactive outputs?

Sometimes, we have interactive outputs from Jupyter notebook cells. Up to now, most places you'd save notebooks, e.g. GitHub/GitLab, only showed a static image instead of the original rich output, and you'd have to open the notebook in Colab, or a similar tool in order to interact with your outputs.

This limits sharability and creates a lossy experience.

Now, when you commit a notebook to DagsHub, its interactive outputs remain just as they would appear in the original notebook even after committing them to git.

This means the results from all the popular data science logging tools can be visualized without having to switch tabs.

All of this comes without changing anything in the code or imports.

Why do I need this?

Since many data scientists use notebooks, and they are generally great for prototyping and creating interactive visualizations that could be shared with your team, we wanted to make those visualizations actually interactive, even after they are committed to Git, that way your team members experience the results exactly as you did.

What is this repository?

This repo showcases some of the things you can do with interactive outputs, for example:

Interactive Data Exploration (EDA)

Use tools like Pandas Profiling or SweetViz, to visualize your data.

Check out the example notebooks:

1. Interactive Pandas Profiling
2. Interactive SweetViz

Interactive Dashboards

You can even view your Weights & Biases dashboard interactively on DagsHub as part of your Jupyter output.

1. Interactive W&B Dashboard

Questions?

If you have questions, found a bug, or have a suggestion reach out to us on our Discord channel