{"library":"prince","type":"library","category":null,"description":"Prince is a Python library for various factor analysis methods, including Principal Component Analysis (PCA), Correspondence Analysis (CA), Multiple Correspondence Analysis (MCA), Multiple Factor Analysis (MFA), Factor Analysis of Mixed Data (FAMD), Generalized Procrustes Analysis (GPA), and Procrustes Global Analysis (PGA). As of version 0.17.0, it offers a scikit-learn compatible API, making it easy to integrate into existing data science workflows. The project is actively maintained with a relatively steady release cadence, incorporating new features and improvements.","language":"python","status":"active","version":"0.17.0","tags":["factor-analysis","pca","mca","data-science","machine-learning","sklearn-compatible"],"install":[{"cmd":"pip install prince","imports":["from prince import PCA","from prince import MCA","from prince import CA","from prince import MFA","from prince import FAMD"]}],"homepage":null,"github":null,"docs":null,"changelog":null,"pypi":"https://pypi.org/project/prince/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":15.3,"avg_import_s":4.76,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/prince/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}