https://github.com/facebookresearch/hiplot

HiPlot makes understanding high dimensional data easy
https://github.com/facebookresearch/hiplot

Last synced: about 1 month ago
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HiPlot makes understanding high dimensional data easy

• Host: GitHub
• URL: https://github.com/facebookresearch/hiplot
• Owner: facebookresearch
• License: mit
• Archived: true
• Created: 2019-11-08T13:06:41.000Z (almost 6 years ago)
• Default Branch: main
• Last Pushed: 2024-01-10T07:43:27.000Z (almost 2 years ago)
• Last Synced: 2025-09-18T17:39:37.459Z (about 2 months ago)
• Language: TypeScript
• Homepage: https://facebookresearch.github.io/hiplot/
• Size: 516 MB
• Stars: 2,801
• Watchers: 27
• Forks: 147
• Open Issues: 20
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

• awesome-list - HiPlot - A lightweight interactive visualization tool to help AI researchers discover correlations and patterns in high-dimensional data. (Data Visualization / Data Management)
• awesome-starred - facebookresearch/hiplot - HiPlot makes understanding high dimensional data easy (others)
• awesome-python-machine-learning-resources - GitHub - 15% open · ⏱️ 05.07.2022): (数据可视化)

README

          
# HiPlot - High dimensional Interactive Plotting [![CircleCI](https://circleci.com/gh/facebookresearch/hiplot/tree/main.svg?style=svg&circle-token=c89b6825078e174cf35bdc18e4ad4a16e28876f9)](https://circleci.com/gh/facebookresearch/hiplot/tree/main)

![Logo](https://raw.githubusercontent.com/facebookresearch/hiplot/main/hiplot/static/logo.png)

[![Support Ukraine](https://img.shields.io/badge/Support-Ukraine-FFD500?style=flat&labelColor=005BBB)](https://opensource.fb.com/support-ukraine)

[![License: MIT](https://img.shields.io/badge/License-MIT-brightgreen.svg)](https://opensource.org/licenses/MIT)

[![PyPI download month](https://img.shields.io/pypi/dm/hiplot.svg)](https://pypi.python.org/pypi/hiplot/) [![PyPI version](https://img.shields.io/pypi/v/hiplot.svg)](https://pypi.python.org/pypi/hiplot/) [![docs](https://img.shields.io/badge/docs-passing-brightgreen.svg)](https://facebookresearch.github.io/hiplot/index.html) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/facebookresearch/hiplot/blob/main/examples/HiPlotColabExample.ipynb)

HiPlot is a lightweight interactive visualization tool to help AI researchers discover correlations and patterns in high-dimensional data using parallel plots and other graphical ways to represent information.

### [Try a demo now with sweep data](https://facebookresearch.github.io/hiplot/_static/demo/ml1.csv.html) or [upload your CSV](https://facebookresearch.github.io/hiplot/_static/hiplot_upload.html)  or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/facebookresearch/hiplot/blob/main/examples/HiPlotColabExample.ipynb)

There are several modes to HiPlot:

- As a web-server (if your data is a CSV for instance)

- In a jupyter notebook (to visualize python data), or in [Streamlit apps](https://facebookresearch.github.io/hiplot/tuto_streamlit.html)

- In CLI to render standalone HTML

```bash

pip install -U hiplot  # Or for conda users: conda install -c conda-forge hiplot

```

If you have a jupyter notebook, you can get started with something as simple as:

```python

import hiplot as hip

data = [{'dropout':0.1, 'lr': 0.001, 'loss': 10.0, 'optimizer': 'SGD'},

        {'dropout':0.15, 'lr': 0.01, 'loss': 3.5, 'optimizer': 'Adam'},

        {'dropout':0.3, 'lr': 0.1, 'loss': 4.5, 'optimizer': 'Adam'}]

hip.Experiment.from_iterable(data).display()

```

### [See the live result](https://facebookresearch.github.io/hiplot/_static/demo/demo_basic_usage.html)

![Result](https://raw.githubusercontent.com/facebookresearch/hiplot/main/assets/notebook.png)

## Links

* Blog post: https://ai.facebook.com/blog/hiplot-high-dimensional-interactive-plots-made-easy/

* Documentation: https://facebookresearch.github.io/hiplot/index.html

* Pypi package: https://pypi.org/project/hiplot/

* Conda package: https://anaconda.org/conda-forge/hiplot

* NPM package: https://www.npmjs.com/package/hiplot

* Examples: https://github.com/facebookresearch/hiplot/tree/main/examples

## Citing

```bibtex

@misc{hiplot,

    author = {Haziza, D. and Rapin, J. and Synnaeve, G.},

    title = {{Hiplot, interactive high-dimensionality plots}},

    year = {2020},

    publisher = {GitHub},

    journal = {GitHub repository},

    howpublished = {\url{https://github.com/facebookresearch/hiplot}},

}

```

## Credits

Inspired by and based on code from [Kai Chang](http://bl.ocks.org/syntagmatic/3150059), [Mike Bostock](http://bl.ocks.org/1341021) and [Jason Davies](http://bl.ocks.org/1341281).

External contributors (*please add your name when you submit your first pull request*):

- [louismartin](https://github.com/louismartin)

- [GoldenCorgi](https://github.com/GoldenCorgi)

- [callistachang](https://github.com/callistachang)

## License

HiPlot is [MIT](LICENSE) licensed, as found in the [LICENSE](LICENSE) file.