Data Formulator

<h1 align="center"> <img src="https://raw.githubusercontent.com/microsoft/data-formulator/main/public/favicon.ico" alt="Data Formulator icon" width="28">&nbsp; Data Formulator: AI-powered Data Visualization </h1> <p align="center"> 🪄 Explore data with visualizations, powered by AI agents. </p> <p align="center"> &nbsp; </p> <p align="center"> <a href="https://github.com/microsoft/data-formulator/actions/workflows/python-build.yml"><img src="https://github.com/microsoft/data-formulator/actions/workflows/python-build.yml/badge.svg" alt="build"></a>&ensp; </p> <!-- [](https://codespaces.new/microsoft/data-formulator?quickstart=1) --> <!-- https://github.com/user-attachments/assets/8ca57b68-4d7a-42cb-bcce-43f8b1681ce2 -->

Why Data Formulator?

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 🔥🔥🔥

[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 data_formulator@0.8.0b1. 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

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

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

Play with Data Formulator with one of the following options.

Desktop downloads

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:

  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