Datapane

Python library for building interactive data reports with plots, tables, and forms — export as HTML or share online.

docs.datapane.com

Verified API available

Quick facts
What is it	Python library for building interactive data reports with plots, tables, and forms — export as HTML or share online.
Pricing	Unknown
Platform	Web Application
API	Yes
Best for	Creating shareable data reports from Jupyter notebooks, Building interactive dashboards for internal teams
Domain registered	2013

Data updated Aug. 1, 2026

What does Datapane do?

Datapane is a Python library that helps you create interactive data reports quickly. You import it into your Python script or notebook, then build reports by wrapping components like Pandas DataFrames, visualizations from libraries like Bokeh or Plotly, Markdown text, and various file types. The reports can include interactive elements like forms that run backend Python functions, and they support multi-page layouts with tabs and drop-down menus.

What makes Datapane stand out is its focus on programmatic report building. Instead of using a GUI, you construct reports through code, which makes the process reproducible and easy to version control. Once created, reports can be exported as standalone HTML files, shared via URL, or embedded into other applications. This lets viewers interact with the data directly—sorting tables, exploring plots, and submitting forms—without needing Python installed.

This tool is most useful for data scientists, analysts, and developers who work in Python and need to share their findings with others. Typical use cases include generating reports from Jupyter notebooks, creating internal dashboards for team review, or publishing data-driven research with interactive elements. While the project is no longer actively maintained, the final release supports local report saving with updated dependencies for continued use.

Data & Analytics — Other

#data sharing#data visualization#html export

Key features

What makes it stand out

Build reports programmatically using Python scripts or notebooks

Embed interactive plots from libraries like Bokeh, Plotly, and Altair

Include Pandas DataFrames as sortable, filterable tables

Add Markdown text, images, PDFs, and other files to reports

Create forms with user inputs that trigger backend Python functions

Who is Datapane for?

Who benefits most from this tool

Creating shareable data reports from Jupyter notebooks

Building interactive dashboards for internal teams

Publishing data findings with embedded visualizations

Trust & presence

Domain Domain registered 2013

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