1. Project Overview & Quickstart (microsoft/data-formulator) Copy Chapter

  Data Formulator: AI-powered Data Visualization

Why Data Formulator? Copy Chapter

Working with data is hard for two simple reasons:

1. Data lives everywhere. Connecting agents to files, databases,
   warehouses, and BI tools takes time. It is even harder when agents start
   answering before the relationships between data sources are clear.
2. Questions evolve as you explore. Each answer can lead to follow-up
   questions, comparisons, and new directions. A long chat history makes it
   hard to see where you are and how you got there.

Data Formulator provides one visual workspace for exploring and analyzing data:

1. Data connectors give agents a common way to connect to different data
   sources and maintains a data memory to remember the relationships between them.
2. Data Threads let you branch into different questions, compare paths,
   and use visualizations to discover deeper insights without losing context.

https://github.com/user-attachments/assets/8e4f8a08-6423-4227-a1f7-559e0126ce31

[!TIP]
Love the charts? They're built on Flint. It's an open-source visualization language that compiles compact chart specs into polished visualizations.

News 🔥🔥🔥 Copy Chapter

[08-15-2026] Data Formulator 0.8 beta 1 (0.8.0b1) introduces:

• One unified flow: load data, ask questions, review results, and branch in the Data Thread.
• More data sources: use files, local folders, databases, and platforms such as Databricks.
• Better charts: explore more Flint-powered charts, recommendations, themes, and styling tools.

Preview with pip install --pre data_formulator==0.8.0b1 or uvx [email protected].
Install the latest stable release (0.7) with pip install data_formulator or run instantly with uvx data_formulator.

See the changelog for release details.

Previous Updates Copy Chapter

Here are milestones that lead to the current design:

• v0.7 (05-28-2026): Turn ANY data into insights in five steps — connect governed data sources, load via agents, explore with the unified DataAgent + Data Thread, refine 30+ chart types (semantic chart engine powered by Flint) with a style-refinement agent, and share as reports. Plus persistent sessions & workspaces and a multilingual (English/Chinese) UI.
• v0.6 (Demo): Real-time insights from live data — connect to URLs and databases with automatic refresh
• uv support: Faster installation with uv — uvx data_formulator or uv pip install data_formulator
• v0.5.1 (Demo): Community data loaders, US Map & Pie Chart, editable reports, snappier UI
• v0.5: Vibe with your data, in control — agent mode, data extraction, reports
• v0.2.2 (Demo): Goal-driven exploration with agent recommendations and performance improvements
• v0.2.1.3/4 (Readme | Demo): External data loaders (MySQL, PostgreSQL, MSSQL, Azure Data Explorer, S3, Azure Blob)
• v0.2 (Demos): Large data support with DuckDB integration
• v0.1.7 (Demos): Dataset anchoring for cleaner workflows
• v0.1.6 (Demo): Multi-table support with automatic joins
• Model Support: OpenAI, Azure, Ollama, Anthropic via LiteLLM (feedback)
• Python Package: Easy local installation (try it)
• Visualization Challenges: Test your skills (challenges)
• Data Extraction: Parse data from images and text (demo)
• Initial Release: Blog | Video

Overview Copy Chapter

Data Formulator is a Microsoft Research project for data exploration with visualizations powered by AI agents. It combines UI interactions with natural language so analysts can communicate intent, branch into alternative analyses, and share results — starting from any data format (screenshot, text, CSV, or database).

Get Started Copy Chapter

Play with Data Formulator with one of the following options.

Desktop downloads Copy Section

CI builds self-contained Windows and macOS applications for pull requests and
every update to main. Download the latest archives from the Artifacts
section of the most recent
desktop builds workflow.
Workflow artifacts are retained for 30 days. Tagged builds are also attached
as permanent downloads to the corresponding
GitHub Release.

Extract the archive, then launch Data Formulator using the instructions for
your operating system:

• Windows: Run Data Formulator.exe. If Microsoft Defender SmartScreen
  appears, select More info, verify that you downloaded the archive from
  this repository, and then select Run anyway.
• macOS: Move Data Formulator.app to Applications. The first time you
  open it, macOS may report that Apple could not verify the app. Open
  System Settings → Privacy & Security, scroll to Security, and select
  Open Anyway for Data Formulator. Confirm by selecting Open when
  prompted.

[!WARNING]
These are automated preview builds and are not currently code-signed or
notarized. Only bypass the operating-system warning when the archive was
downloaded directly from this repository's workflow artifacts or releases.

• Option 1: Install via uv (recommended)

  uv is an extremely fast Python package manager. If you have uv installed, you can run Data Formulator directly without any setup:

  bash Copy

  uvx data_formulator

  Run uvx data_formulator --help to see all available options, such as custom port, sandboxing mode, and data storage location.

• Option 2: Install via pip

  Use pip for installation (recommend: install it in a virtual environment).

  bash Copy

  pip install data_formulator # install
  python -m data_formulator # run

  Data Formulator will be automatically opened in the browser at http://localhost:5567.

• Option 3: Run with Docker

  bash Copy

  docker compose up --build

  Open http://localhost:5567 in your browser. To stop, press Ctrl+C or run docker compose down.

• Option 4: Working as developer

  You can build Data Formulator locally and develop your own version. Check out details in DEVELOPMENT.md.

Using Data Formulator Copy Chapter

Start with the data you already have: upload CSV, TSV, Excel, JSON, screenshots,
or text; connect to databases and data platforms; or ask the analyst to find and
load the data you need. The analyst can discover sources, clarify your request,
propose a loading plan, and let you review the data before adding it to the
workspace.

Continue the conversation in the Data Thread. Ask questions in
natural language and follow the reasoning through explanations, tables, and
editable charts in one history. Refine a result directly, branch from any
earlier step to explore an alternative, or delegate the next investigation to
the analyst. When the analysis is ready, compose the results into a report to
share.

https://github.com/user-attachments/assets/164aff58-9f93-4792-b8ed-9944578fbb72

Contributing Copy Chapter

This project welcomes contributions and suggestions. Most contributions require you to
agree to a Contributor License Agreement (CLA) declaring that you have the right to,
and actually do, grant us the rights to use your contribution. For details, visit
https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need
to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the
instructions provided by the bot. You will only need to do this once across all repositories using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct.
For more information see the Code of Conduct FAQ
or contact [email protected] with any additional questions or comments.

Trademarks Copy Chapter

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft
trademarks or logos is subject to and must follow
Microsoft's Trademark & Brand Guidelines.
Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.
Any use of third-party trademarks or logos are subject to those third-party's policies.

2. Official Technical Reference & Guides (microsoft/microsoft.github.io) Copy Chapter

[microsoft.github.io](https://microsoft.github.io)

Many open source projects released by Microsoft products, services and teams also have
deployments powered by GitHub Pages on this domain.

To discover Microsoft-released open source projects, learn about Microsoft's open source
approach and other information, check us out online at opensource.microsoft.com.

If we can help answer questions about the open source program at Microsoft, you can
contact opensource at microsoft com - although we are not able to provide support
for projects through this mechanism.

Microsoft GitHub resources Copy Chapter

• Default repo templates including SECURITY.MD and code of conduct files: microsoft/repo-templates
• Code of Conduct (FAQ)

Microsoft open source resources Copy Chapter

• Open Source Blog
• The Open Source Show on Channel 9
• https://opensource.microsoft.com/

Resources for Microsoft employees Copy Chapter

• docs.opensource.microsoft.com
• Link your GitHub Account and join GitHub organizations automatically

How to identify an official Microsoft organization on GitHub Copy Chapter

• Official Microsoft GitHub orgs have a professional avatar and include a web address at Microsoft.com or an associated official domain
• Official Microsoft orgs are Verified on GitHub - look for the domain verification indicator on GitHub