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 |
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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 data from a CSV file into Unity Catalog, load data into a DataFrame, and visualize data using Python, Scala, and R. | |
Learn the basics of conducting exploratory data analysis (EDA) using Python in a notebook, from loading data to generating insights. | |
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 |
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Learn the basics for how to effectively use and edit notebooks, including cell types, keyboard shortcuts, and essential editing features. | |
Write and execute code using Python, SQL, Scala, and R with syntax highlighting and IntelliSense. | |
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 |
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Export notebooks in various formats and import notebooks from external sources. | |
Share notebooks, use comments, and collaborate in real-time with your team members. | |
Build and share interactive dashboards directly from your notebook results. |
Debug and optimize your code
Ensure your notebooks run smoothly and efficiently.
Topic | Description |
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Get AI-assisted coding help to debug and write better code faster with intelligent suggestions and explanations. | |
Use the interactive debugger to troubleshoot and fix issues in your notebook code. | |
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 |
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Add interactive input parameters to your notebooks and dashboards using widgets. | |
Manage cell outputs, work with results tables, apply filters, and download data from your notebook results. | |
Learn techniques for orchestrating notebook workflows and modularizing code. | |
Follow recommended practices for efficient and maintainable notebook development. |