How to export a Jupyter notebook using Deepnote

For those diving into data science, utilizing Jupyter notebooks for your projects can be incredibly powerful. As part of your learning journey, you might need to export these notebooks for collaboration, backup, or presentations. In this guide, tailored for data science students, we will delve into how you can export a Jupyter notebook using Deepnote, a collaborative data science notebook platform.

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Prerequisites

Before you begin, ensure that you have the following:

• An active account on Deepnote.
• A Jupyter notebook (.ipynb file) ready to be exported.

Step-by-step guide

Step 1: Open your Jupyter notebook in Deepnote

Log into your Deepnote account and access the Jupyter notebook that you wish to export.

Step 2: Check your notebook

Before exporting, make sure your notebook is complete and has all your final changes. Run through the cells to ensure everything operates as expected.

Step 3: Access export options

With your notebook open:

1. Click on the `File` menu located in the top-left corner of the toolbar.
2. In the dropdown menu that appears, hover over the `Export` option.

Step 4: Select export type

Deepnote offers various options for exporting your notebook. You can choose to export it as:

1. A PDF - ideal for generating readable reports or for print.
2. A .ipynb file - if you're aiming to share it with peers who may wish to run the Jupyter notebook themselves.
3. Other formats such as Markdown, HTML, or even .py (Python script) as per your needs.

Step 5: Initiate export

After selecting the desired export format, Deepnote will prepare the file. If there are any additional prompts, follow them to refine your export settings.

Step 6: Download the file

Once Deepnote finishes the export process, the file will be downloaded to your computer's default download folder. Ensure the file is properly saved.

Step 7: Share or archive your notebook

The exported file can now be shared with classmates, instructors, or incorporated into your project documentation. You can also upload it to a cloud storage service for backup or future references.

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Tips for successful export

• Consistency: Make sure all the code cells are executed in order and display the latest output before exporting.
• Annotations: Include comments and markdown cells for clarity, especially when sharing with others.
• Performance: For large datasets or complex computations, consider clearing the output before exporting to reduce file size.

By following these steps, you can efficiently export your Jupyter notebooks using Deepnote. Understand the importance of choosing the right file format for your purpose and remember that exporting is a great way to showcase your analytical work. Good luck, and happy data analyzing!

Remember, consistent practice is key to mastering data science tools, so use this guide as a resource whenever you need to export your Jupyter notebooks in the future!