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How to use Jupyter with Tableau

By Nick Barth

Updated on March 6, 2024

Jupyter Notebooks offer a versatile platform for data analysis with the Python programming language, and when combined with Tableau's robust data visualization capabilities, they form a powerful toolset for data scientists. To use Jupyter with Tableau, you can follow these steps: 

  1. Prepare your data analysis: Perform your data analysis in Jupyter Notebook using appropriate Python libraries such as pandas and numpy.
  2. Export data from Jupyter: Upon analysis completion, export the processed data to a CSV file or directly to a database.
  3. Connect Tableau to your data source: Open Tableau and connect to the data source where your Jupyter output is stored.
  4. Create visualizations: Utilize Tableau's drag-and-drop interface to create visualizations, dashboards, and reports based on the Jupyter Notebook's data output.
  5. Refresh data: Set up data refresh schedules in Tableau if your Jupyter Notebook runs regularly and updates the data source.

By integrating Jupyter's analytical power with Tableau's visualization strengths, you can make the most out of your data, gaining deeper insights and sharing them in a more intuitive and impactful way.

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