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Databricks notebooks

Notebooks are the primary tool for creating data science and machine learning workflows on Azure 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.

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.

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.