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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.

Demo of Databricks notebook

Get started with notebooks

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

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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.

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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.

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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.

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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.

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

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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.