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How to use Jupyter with PowerBI

By Nick Barth

Updated on March 6, 2024

Integrating Jupyter notebooks with Power BI and Deepnote can greatly enhance data analysis and visualization capabilities. To accomplish this, follow these steps:

  1. Install Power BI Personal Gateway: Ensure that the Power BI Personal Gateway is installed on your machine, as this allows for automatic data refresh from Jupyter notebooks hosted on your local server.
  2. Prepare Jupyter notebook: Develop your analysis in a Jupyter notebook and make sure to output the data in a format that is supported by Power BI (e.g., CSV, JSON).
  3. Publish Jupyter notebook to a web server: Host your Jupyter notebook on a web server or a service like GitHub so that Power BI and Deepnote can access the updated data through an HTTPS link.
  4. Connect to the Jupyter notebook from Power BI: In Power BI, use the 'Web' data connector to connect to the hosted notebook. Enter the URL of the notebook, and Power BI will extract the data from it.
  5. Schedule data refresh: Configure the dataset within Power BI to refresh at regular intervals, syncing it with updates made to the Jupyter notebook.
  6. Create reports and dashboards: Using Power BI's tools, create interactive reports and dashboards based on the data extracted from the Jupyter notebook.
  7. Share insights: Share your Power BI reports and dashboards with others in your organization, enabling them to gain insights from your Jupyter notebook-based analyses.

Note: Deepnote can be integrated with Power BI to enhance collaboration and data analysis workflows.

Nick Barth

Product Engineer

Nick has been interested in data science ever since he recorded all his poops in spreadsheet, and found that on average, he pooped 1.41 times per day. When he isn't coding, or writing content, he spends his time enjoying various leisurely pursuits.

Follow Nick on LinkedIn and GitHub

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