Share a data app from Jupyter in 3 simple steps
Install Datapane's open source library in any Python environment.
pip
conda
Create a free account and run the following code to automatically authenticate your Notebook's environment with Datapane Cloud.
Create a data app from the plots, data, and text in your Jupyter notebook. Host it for free on Datapane Cloud and share with your team.
Analyze in Python, share with Datapane
Python and Jupyter is great for analysis, bad for sharing
Python and Jupyter is the most powerful way to analyze data, but it's not accessible to the people you need to share insights with.
Wow stakeholders with beautiful apps which showcase insights
With Datapane, you can analyze data using the libraries and tools you love, and turn them into beautiful apps your stakeholders can use in seconds.
Community
Join a passionate community of app builders
Datapane is used by passionate individuals and forward-thinking companies to build data apps in a code-first, open-source way. Join our Discord to say hi.
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Serverless
Unique architecture for exceptional data apps
Datapane's serverless architecture means you can build data apps from inside the tools you love without thinking about infrastructure and hosting.
Build apps from Jupyter, Airflow, or Spark.
Dynamic 100% serverless components
No infrastructure or complex back-end.
Export as super-fast, pre-rendered HTML.
“Datapane’s open-source framework allows us to use the full power of Python to create HR analytics reports for stakeholders. We build things we could never create in a UI-first tool, and can automate the whole process in a fraction of the time.”
Matthew Fein
People Scientist, Oscar Health
People Scientist, Oscar Health
“We use Datapane as the front-end for our machine learning monitoring framework, Eurybia. It makes it easy to create beautiful interactive reports to instrument our models and data.”
Thomas Bouche
Data Scientist, MAIF
Data Scientist, MAIF
“Datapane is a speedy way to generate complex visualizations, and share these with non-technical people. It’s a cool tool that plugs right into our ML stack.”
Marian Andrecki
Machine Learning Engineer, Proportunity
Machine Learning Engineer, Proportunity
Blocks & Components
A complete set of building blocks for data apps
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