Create and share interactive reports from Python

Datapane's API makes it easy to build hosted, interactive reports, straight from your existing Python environment.

Python reports

An API for turning analyses into reports

Sharing Python analyses is painful. Datapane makes it easy by allowing you to turn your existing notebooks and scripts into self-service reporting tools.

An API for data developers

Instead of learning another enterprise tool, build reports from DataFrames and plots in Python, or deploy your script so stakeholders can generate reports dynamically.

  • 1
    Analyse data in your own tools

    Write code and analyse data in your existing environment, such as Jupyter, instead of a being forced to use Yet Another BI Platform.

  • 2
    Create reports in code

    Use Datapane's API to build and share reports from DataFrames, Markdown, and visualisation libraries, such as Bokeh and Altair.

  • 3
    Deploy and share

    Want to make your report dynamic? Deploy your script to let stakeholders pass in parameters and run reports in their browser.

  1. import pandas as pd
  2. import datapane as dp
  3. import altair as alt
  4. import yfinance as yf
  5. input_stock = dp.parameters.stock
  6. data ="msft aapl goog amzn {input_stock}", period="max")
  7. df = data['Close'].reset_index().melt('date', var_name='symbol', value_name='price')
  8. plot = alt.Chart(df).encode(x='Date', y='symbol', color='price').mark_line().interactive()
  9. def render():
  10. return [dp.Table(df), dp.Plot(plot)]

A self-service interface for stakeholders

Stakeholders can view reports in their browser, or generate and schedule reports dynamically using forms.

  • Forms

    Enter input parameter to scripts using web forms, in order to generate reports dynamically.

  • Embed & Share

    Share reports with others, or embed into your internal tools, such as Confluence and Notion, or your own website.

  • Schedule (Coming Soon)

    Schedule your scripts to run on a cadence, to automatically generate reports for stakeholders.


Simple pricing for teams.

Want to use Datapane in your team? Choose one of our paid plans or get in touch.

$450 / month

Up to 20 named users. Securely share analyses with stakeholders in your own hosted instance.

  • Private Hosted Instance

  • Unlimited Scripts & Reports

  • Datapane Branded Embedding

  • Warehouse and API Integration

Contact Us

Unlimited users. Deploy and integrate Datapane into your organisation and applications.

  • Scheduling (Coming Soon)

  • On-premise Deployment

  • White-label Embedding

  • Granular Access Controls

Want to use Datapane for hosting and sharing your public analyses? Datapane's public instance is free for individuals.

What can you build with Datapane?

Teams use Datapane to share data science models, product and sales analytics, financial forecasts, and more!

Product Analytics
Product Analytics

Python excels at product analytics techniques such as market basket analysis, A/B testing, and segmentation. Datapane makes it easy for PMs to self-serve on these analyses.

Sunset in the mountains
Hosted ML Models

Train machine learning models on your own infrastructure, and use Datapane to provide an accessible front-end so your whole company can self-serve on data science in their browser.

Sunset in the mountains
Social Embedding

Use Datapane's free public instance to upload notebooks and scripts and share results with your community. Embed interactive visualisations and explorable datasets into a blog or website.

Frequently asked questions

Where are my scripts hosted and run?

Datapane provides a public instance for individuals, private instances for teams, or an on-premise deployment which you can run on your own infrastructure.

Can scripts on Datapane talk to databases and APIs?

Yes. Once on Datapane, your code has network access and can connect to third-party systems, so can push or pull from a database or API.

I already have data infrastructure for resource intensive tasks, like model training. Do I have to run this on Datapane?

No. Datapane's philosophy is to fit into your existing infrastructure, and provides an API to push assets (such as trained models) from other platforms so you can access them in your scripts.

What libraries can my script use on Datapane?

Datapane supports the majority of Python visualisation libraries, such as Bokeh, Altair, and Matplotlib, and many Python analysis libraries. On paid plans, you can provide your own libraries or a Docker image which your code will run in.

Can I generate static reports from Airflow, a hosted Jupyter, or my local Python environment?

Yes. If you don't need to interactive scripts which generate reports dynamically, you can create reports directly from your existing Python environment, without running code on Datapane.

Where can I embed reports?

In addition to iframe support, you can embed reports directly into Reddit, Medium, Notion, and more.

Ready to get started?
Get in touch or create an account.

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