Metadata-Version: 2.4
Name: pyemb
Version: 1.0.0a13
Summary: EDA for complex data
Project-URL: Documentation, https://pyemb.github.io/pyemb
Project-URL: Repository, https://github.com/pyemb/pyemb
Author-email: Annie Gray <annie.gray@bristol.ac.uk>, Ed Davis <edward.davis@bristol.ac.uk>
License: MIT
License-File: LICENSE
Keywords: EDA,embedding
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.10
Requires-Dist: matplotlib>=3.9.1.post1
Requires-Dist: networkx>=3.3
Requires-Dist: numpy>=2.0.1
Requires-Dist: pandas>=2.2.2
Requires-Dist: requests>=2.32.3
Requires-Dist: scikit-learn>=1.5.1
Requires-Dist: scipy==1.14.1
Requires-Dist: tqdm>=4.66.4
Provides-Extra: doc
Requires-Dist: setuptools>=59.6.0; extra == 'doc'
Requires-Dist: sphinx; extra == 'doc'
Provides-Extra: embed
Requires-Dist: numba>=0.60.0; extra == 'embed'
Provides-Extra: hc
Requires-Dist: fa2-modified>=0.3.10; extra == 'hc'
Requires-Dist: pygraphviz>=1.13; extra == 'hc'
Provides-Extra: nlp
Requires-Dist: nltk>=3.8.1; extra == 'nlp'
Requires-Dist: textblob>=0.18.0.post0; extra == 'nlp'
Provides-Extra: plotting
Requires-Dist: plotly>=5.22.0; extra == 'plotting'
Provides-Extra: wasserstein
Requires-Dist: pot>=0.9.4; extra == 'wasserstein'
Description-Content-Type: text/markdown

# pyemb - EDA of embeddings in Python

pyemb is a toolkit for analysing complex datasets through the lens of embedding high-dimensional data, relational databases and networks. It includes functionality for preprocessing, various embedding techniques, hierarchical clustering and visualisation. The aim of this package is have implementations of an variety of exploratory data anaylsis tools that can be used across a large array of datasets. 

To install the package, you can use pip: `pip install pyemb`

Code has been tested for python versions 3.10 to 3.13 on Ubuntu and Mac. 

