Jupyter is a fantastic tool for analyzing data. It makes compiling and managing data projects more fun and more efficient.
It’s become the de facto development environment for most data scientists, and the broader ecosystem of tools and libraries has made analyzing data 10x better.
Unfortunately, it falls short when it comes to sharing the valuable output of a project with someone who isn’t technical.
Seeing inside a Notebook, messy code and all, is hardly a wow moment. On the contrary, it distracts from the valuable insights they need and that we want to share.
Many end up sharing their work as underwhelming PowerPoint slides or exporting notebooks as static HTML files or PDFs. (...which then means manually re-exporting every time they need to make a change).
Spinning up a Notebook into a data app with Datapane bridges this gap.
Our Jupyter-to-app conversion lets you take any Jupyter Notebook and transform it into a web app in seconds.
Once you import Datapane’s open-source Python library, all it takes is a single line of code.
To get started, import datapane to your notebook and login:
Once you've added your cells, save your notebook before running the app conversion code:
Remember to use .upload to upload it to Cloud or .save to create a local file. You can read all about it here in our docs.
It should look something like this:
Existing users may need to upgrade to the latest version of Datapane first.
We think that converting Jupyter into a web app gives data scientists the sharing superpowers they’ve lacked.
Why? It saves time and effort, so you can spend more time in Python and less time in PowerPoint.
But more importantly, it makes receiving insights a wow moment for non-technical audiences.
In other words, we think unlocking your notebook as a web app can denoise your analysis, so it makes the impact it deserves.
Try it out and let us know what you think.