microsoft/data-formulator sits at 16.0k stars on GitHub, written primarily in Python. πͺ Data Formulator is an interactive AI-powered data analysis system makes it easy to connect, explore and visualize data.
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πͺ Explore data with visualizations, powered by AI agents.
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Why Data Formulator?
Your data lives everywhere β databases, warehouses, BI tools, files. Coding agents can help, but only after someone wires them up, and answers come back as walls of code or text that are hard to follow, refine, or share.
Data Formulator makes it simple: connect any data, ask anything, get charts you can edit, branch, and share β all on one interactive, visual canvas.
Data & platform teams: wire up your databases, warehouses, and BI sources once, and give the whole org an AI-powered data exploration layer.
Analysts & users: ask, edit, branch, share. It's so easy to get insights from good-looking charts.
[!TIP]
Love the charts? They're built on Flint β our open-source visualization language that compiles compact, semantic chart specs into polished Vega-Lite, ECharts, and Chart.js. Explore the project site or drop it into your own app.
News π₯π₯π₯
[07-23-2026] Data Formulator 0.8 alpha (a1βa4, latest: 0.8.0a4) includes:
Conversational database loading. Agents can discover relevant tables, propose filters, preview results, and revise a loading plan through conversation before importing data.
Unified Data Thread. Questions, clarifications, explanations, tables, and charts share one conversation history, with branching from earlier steps into new questions, calculated columns, or visualizations.
Expanded chart gallery, powered by Flint. New bullet, connected scatter, ECDF, Gantt, range area, slope, sparkline, and violin charts, along with improved chart recommendations. Try the open-source Flint chart language in your own applications.
Persistent analyst attachments. CSV, JSON, Excel, and other attached files remain available to the analyst throughout an exploration instead of being embedded once in a prompt.
Databricks connector. Browse Unity Catalog catalogs, schemas, and tables, then load Databricks data into the exploration workflow.
Microsoft authentication for enterprise connectors. SQL Server supports passwordless Microsoft Entra ID authentication through az login, including an in-app flow for local deployments. Kusto supports delegated Microsoft sign-in alongside Azure default identity and service principal authentication.
Connector setup and diagnostics. Connection forms separate connection, scope, and source-specific authentication options. Persistent server logs and an in-app log viewer help diagnose failures.
Preview with pip install --pre data_formulator==0.8.0a4 or uvx [email protected].
Install the latest stable release (0.7) with pip install data_formulator or run instantly with uvx data_formulator.
Previous Updates
Here are milestones that lead to the current design:
v0.7 (05-28-2026): Turn ANY data into insights in five steps β 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.
v0.7 alpha 2 (05-11-2026): Early preview of data connectors, the unified DataAgent with thread memory, persistent workspaces, the semantic chart engine, and experimental knowledge distillation.
v0.6 (Demo): Real-time insights from live data β connect to URLs and databases with automatic refresh
uv support: Faster installation with uv β 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 β 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
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 β starting from any data format (screenshot, text, CSV, or database).
Get Started
Play with Data Formulator with one of the following options.
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:
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).
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
docker compose up --build
Open http://localhost:5567 in your browser. To stop, press Ctrl+C or run docker compose down.
Option 4: Codespaces
You can run Data Formulator in Codespaces; we have everything pre-configured. For more details, see CODESPACES.md.
Option 5: Working as developer
You can build Data Formulator locally and develop your own version. Check out details in DEVELOPMENT.md.
Using Data Formulator
Besides uploading csv, tsv or xlsx files that contain structured data, you can ask Data Formulator to extract data from screenshots, text blocks or websites, or load data from databases use connectors. Then you are ready to explore. Ask visualizaiton questions, edit charts, or delegate some exploration tasks to agents. Then, create reports to share your insights.
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
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.
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How active is development on microsoft/data-formulator?
The most recent commit recorded on microsoft/data-formulator was 11 days ago, based on the GitHub push timestamp. The repository has 1.5k forks β one of the better signals of community interest.
How many stars does microsoft/data-formulator have?
microsoft/data-formulator has 16.0k GitHub stars β refresh the page for the live number, or check github.com/microsoft/data-formulator. TopGit mirrors GitHub's count but does not claim minute-by-minute accuracy.
Is microsoft/data-formulator open source?
Yes β microsoft/data-formulator ships under the MIT license, which makes its source code freely readable (and, depending on license terms, forkable and reusable). Source: github.com/microsoft/data-formulator.
Where can I see microsoft/data-formulator in action?
The project maintains a homepage at https://data-formulator.ai/. The README tab on this page also usually contains screenshots and a quickstart.
Where do I read more about microsoft/data-formulator?
This TopGit page is a snapshot β the READ ME tab shows the project's own README content (links stripped, images preserved). The GitHub repository at github.com/microsoft/data-formulator is the definitive source.
Read full README in the tab above.
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