sissa-data-science/DADApy
Distance-based Analysis of DAta-manifolds in python
This tool helps scientists and researchers understand the hidden structure of complex, high-dimensional datasets. It takes raw numerical data, such as experimental measurements or simulation outputs, and analyzes its intrinsic properties like dimensionality, density, and natural groupings. The output provides insights into how many meaningful variables truly describe the data, where data points cluster, and how different datasets relate to each other, aiding in data exploration and hypothesis generation.
142 stars. Available on PyPI.
Use this if you are working with large, complex datasets and need to uncover their underlying structure, identify natural clusters, or determine the true complexity of the information they contain.
Not ideal if you need simple statistical summaries, basic visualizations, or direct feature engineering for machine learning models without exploring the manifold characteristics first.
Stars
142
Forks
23
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 13, 2026
Commits (30d)
0
Dependencies
10
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