{"library":"pca","type":"library","category":null,"description":"pca is a Python package for Principal Component Analysis (PCA), providing extended functionality beyond basic scikit-learn implementations. It leverages sklearn's core for compatibility while offering features like SparsePCA and TruncatedSVD, comprehensive analysis, and advanced plotting capabilities such as biplots, explained variance plots, outlier detection, and feature importance extraction. The current version is 2.10.2, and it is actively maintained.","language":"python","status":"active","version":"2.10.2","tags":["PCA","dimensionality reduction","machine learning","data analysis","visualization","scikit-learn wrapper","outlier detection"],"install":[{"cmd":"pip install pca","imports":["from pca import pca","from sklearn.decomposition import PCA"]}],"homepage":"https://erdogant.github.io/pca","github":"https://github.com/erdogant/pca","docs":null,"changelog":null,"pypi":"https://pypi.org/project/pca/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":21.1,"avg_import_s":6.59,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/pca/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}