Databricks notebooks

Notebooks are the primary tool for creating data science and machine learning workflows on Databricks. Databricks notebooks provide real-time coauthoring in multiple languages, automatic versioning, and built-in data visualizations for developing code and presenting results.

Get started with notebooks

Get hands-on experience with step-by-step tutorials that guide you through common use cases.

Topic	Description
Query and visualize data from a notebook	Learn data science basics by using a notebook to query and visualize sample data stored in Unity Catalog using SQL, Python, Scala, and R.
Import and visualize CSV data from a notebook	Import data from a CSV file into Unity Catalog, load data into a DataFrame, and visualize data using Python, Scala, and R.
EDA techniques using Databricks notebooks	Learn the basics of conducting exploratory data analysis (EDA) using Python in a notebook, from loading data to generating insights.
End-to-end classic ML models	Complete tutorial for training classic machine learning models, including data loading, visualization, hyperparameter optimization, and MLflow integration.

Develop and run notebooks

Learn the fundamentals of creating and using notebooks in your Databricks workspace.

Topic	Description
Basic editing	Learn the basics for how to effectively use and edit notebooks, including cell types, keyboard shortcuts, and essential editing features.
Develop code in notebooks	Write and execute code using Python, SQL, Scala, and R with syntax highlighting and IntelliSense.
Run notebooks	Execute notebooks and individual cells with flexible compute options and execution controls.

Collaborate and share your work

Work together with your team and share your results effectively.

Topic	Description
Import and export notebooks	Export notebooks in various formats and import notebooks from external sources.
Collaborate using notebooks	Share notebooks, use comments, and collaborate in real-time with your team members.
Dashboards in notebooks	Build and share interactive dashboards directly from your notebook results.

Debug and optimize your code

Ensure your notebooks run smoothly and efficiently.

Topic	Description
Code help using Databricks Assistant	Get AI-assisted coding help to debug and write better code faster with intelligent suggestions and explanations.
Debug notebooks	Use the interactive debugger to troubleshoot and fix issues in your notebook code.
Unit testing	Implement unit testing strategies to validate your notebook code and ensure reliability.

Popular pages

Explore commonly referenced topics and advanced features for working with notebooks.

Topic	Description
Databricks widgets	Add interactive input parameters to your notebooks and dashboards using widgets.
Notebook outputs and results	Manage cell outputs, work with results tables, apply filters, and download data from your notebook results.
Orchestrate notebooks and modularize code	Learn techniques for orchestrating notebook workflows and modularizing code.
Best practices	Follow recommended practices for efficient and maintainable notebook development.