Transform data and create rich visualizations iteratively with AI 🪄. Try Data Formulator now in GitHub Codespaces!
Data Formulator is an application from Microsoft Research that uses large language models to transform data, expediting the practice of data visualization.
To create rich visualizations, data analysts often need to iterate back and forth among data processing and chart specification to achieve their goals. To achieve this, analysts need proficiency in data transformation and visualization tools, and they also spend effort managing the iteration history. This can be challenging!
Data Formulator is an AI-powered tool for analysts to iteratively create rich visualizations. Unlike most chat-based AI tools where users need to describe everything in natural language, Data Formulator combines user interface interactions (UI) with natural language (NL) inputs. This blended approach makes it easier for users to describe their chart designs while delegating data transformation to AI.
Check out these cool Data Formulator features that can help you create impressive visualizations!
- Using the blended UI and NL inputs to describe the chart.
- Utilizing data threads to navigate the history and reuse previous results to create new ones instead of starting from scratch every time.
Choose one of the following options to set up Data Formulator:
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Option 1: Codespaces
Use Codespaces for an easy setup experience, as everything is preconfigured to get you up and running quickly. For more details, see CODESPACES.md.
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Option 2: Local Installation
Opt for a local installation if you prefer full control over your development environment and the ability to customize the setup to your specific needs. For detailed instructions, refer to DEVELOPMENT.md.
Once you’ve completed the setup using either option, follow these steps to start using Data Formulator:
- Provide OpenAI keys and select a model (GPT-4o suggested) and choose a dataset
- Choose a visualization type
- Drag and drop data fields to the encoding shelf to create visualization
renewable.mp4
- Add new field names in the encoding shelf, describe the chart intent
- Click the Formulate button
- Inspect the code behind the concept
- Follow up the chart to create new ones
renewable-pct.mp4
renewable-rank.mp4
Repeat this process as needed to explore and understand your data. Your explorations are trackable in the Data Threads panel.
Follow the developers' instructions to build your new data analysis tools on top of Data Formulator.
@article{wang2024dataformulator2iteratively,
title={Data Formulator 2: Iteratively Creating Rich Visualizations with AI},
author={Chenglong Wang and Bongshin Lee and Steven Drucker and Dan Marshall and Jianfeng Gao},
year={2024},
booktitle={ArXiv preprint arXiv:2408.16119},
}
@article{wang2023data,
title={Data Formulator: AI-powered Concept-driven Visualization Authoring},
author={Wang, Chenglong and Thompson, John and Lee, Bongshin},
journal={IEEE Transactions on Visualization and Computer Graphics},
year={2023},
publisher={IEEE}
}
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 opencode@microsoft.com with any additional questions or comments.
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