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How to turn a Juptyer notebook into an app

By Nick Barth

Updated on March 6, 2024

Turning a Jupyter notebook into an app with Deepnote is a simple yet powerful way of sharing your interactive data analysis with users who may not be familiar with Jupyter or programming in general. Follow these steps:

  1. Prepare your notebook: Begin by ensuring that your Jupyter notebook is clear, well-documented, and has a user-friendly structure. Define variables, functions, and user inputs at the top for easy accessibility.
  2. Sign up or log in to Deepnote: Go to Deepnote and sign up for an account or log in if you already have one.
  3. Import your notebook: Click on 'New Project' and import your Jupyter notebook into Deepnote by uploading the `.ipynb` file or connecting to your GitHub repository where the notebook is stored.
  4. Refine the notebook: Use Deepnote's built-in tools to refine your notebook. Convert sections of your notebook into dashboard cells by clicking the dashboard icon on the selected cells. This allows you to hide the code and showcase only the results or interactive widgets.
  5. Set up variables for user input: Define variables that users can interact with. Deepnote's variable editor allows users to modify inputs without interacting with the code directly.
  6. Share the project: After setting up, click on the 'Share' button at the top of the Deepnote project. Here, you can decide to make the project public, invite collaborators, or define access levels.
  7. Launch as an app: Finally, use the 'Launch' feature to turn your notebook into a web app. You can choose to launch just a dashboard, which displays the output cells and widgets as a standalone page, or the entire notebook.

By converting a Jupyter notebook into an app with Deepnote, you democratize the access to complex data analyses, allowing stakeholders with no coding background to interact with the data and draw insights effectively. This approach bridges the gap between data scientists and decision-makers by providing a user-friendly interface for interactive data visualization.

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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