Getting started with Snowflake Notebooks¶

To start experimenting with Snowflake Notebooks, sign into Snowsight, set up your account to use notebooks, and then select Projects » Notebooks. A list of notebooks that you have access to in your account is displayed. You can either create a new notebook from scratch or upload an existing .ipynb file.

The following table shows the topics to review if you’re new to Snowflake Notebooks:

Getting started guides
	Setting up Snowflake Notebooks Instructions for developers and admins before using Notebooks.
	Create a notebook Create a new notebook from scratch or from an existing file.
	Develop and run code in Snowflake Notebooks Create, edit, execute Python, SQL, and Markdown cells.

Developer guides¶

Guide	Description
Session context in notebooks	Accessing and modifying the session context.
Saving results in notebooks	Saving notebooks and results across sessions.
Import Python packages to use in notebooks	Importing Python packages from Anaconda channel.
Visualize and Interact with your data in Notebook	Visualize data with matplotlib, plotly, or altair, and develop a data app with Streamlit.
Cell and variable referencing in Notebook	Reference SQL cell output and Python variable values.
Keyboard shortcuts for Notebooks	Leverage keyboard shortcuts to navigate and streamline the editing experience.

Leveling up your notebook workflows¶

Guide	Description
Sync Snowflake Notebooks with Git	Version control your notebook for collaboration and development.
Work with files in notebooks	Manage and work with files in your notebook environment.
Schedule notebook runs	Schedule notebooks to run and execute code within Snowflake.
Troubleshoot errors in Snowflake Notebooks	Troubleshoot errors that may occur while you’re using Snowflake Notebooks.

Quickstarts¶

Getting Started with Your First Snowflake Notebook [Video] [Source]

Learn how to get started with your first notebook project in less than 10 minutes.
Visual Data Stories with Snowflake Notebooks [Video] [Source]

Learn how you can create compelling data narratives using visualizations, Markdown, images, and interactive data apps all within your notebook, alongside your code and data.

Highlighted use cases¶

Check out highlighted use cases for data science, data engineering, and ML/AI in Github.

Getting started guides¶
Guide	Description
	Setting up Snowflake Notebooks Instructions for developers and admins before using Notebooks.
	Create a notebook Create a new notebook from scratch or from an existing file.
	Develop and run code in Snowflake Notebooks Create, edit, and execute Python, SQL, and Markdown cells.

Note

These quickstarts are only shown as examples. Following along with the example may require additional rights to third-party data, products, or services that are not owned or provided by Snowflake. Snowflake does not guarantee the accuracy of these examples.

Additional resources¶

For notebook demos, tutorials, and examples, see the collection of Snowflake Notebooks demos in GitHub.
To view tutorial videos, see the Snowflake Notebooks YouTube playlist.
To learn about SQL commands to create, execute, and show notebooks, see Snowflake Notebooks API reference.
Looking for reference architectures, industry-specific use cases and solutions best practices using Notebooks? See Notebooks examples in the Snowflake Solution Center.