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HyperTools is a library for visualizing and manipulating high-dimensional data in Python. It is built on top of matplotlib (for plotting), seaborn (for plot styling), and scikit-learn (for data manipulation). Functions for plotting high-dimensional datasets in 2/3D. Static and animated plots. Simple API for customizing plot styles. Set of powerful data manipulation tools including hyperalignment, k-means clustering, normalizing and more. Support for lists of Numpy arrays, Pandas dataframes, text or (mixed) lists. Applying topic models and other text vectorization methods to text data. HyperTools is designed to facilitate dimensionality reduction-based visual explorations of high-dimensional data. The basic pipeline is to feed in a high-dimensional dataset (or a series of high-dimensional datasets) and, in a single function call, reduce the dimensionality of the dataset(s) and create a plot.
Features
- Check the repo of Jupyter notebooks from the HyperTools paper
- Click the badge to launch a binder instance with example uses
- The package is built atop many familiar friends, including matplotlib, scikit-learn and seaborn
- Requires python>=3.6
- Requires scikit-learn>=0.24.0
- Requires seaborn>=0.8.1
Project Samples
