{"repo":"MaxHalford/prince","free":true,"listed":false,"github":"https://github.com/MaxHalford/prince","clone":"git clone https://github.com/MaxHalford/prince.git","description":":crown: Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA","language":"Python","stars":1479,"topics":["pandas","pca","ca","mca","python","svd","factor-analysis","correspondence-analysis","principal-component-analysis","scikit-learn"],"license":"MIT","category":"dev-tools","readme_excerpt":"Prince is a Python library for multivariate exploratory data analysis in Python. It includes a variety of methods for summarizing tabular data, including principal component analysis (PCA) and correspondence analysis (CA). Prince provides efficient implementations, using a scikit-learn API. I made Prince when I was at university, back in 2016. I spent a significant amount of time in 2022 to revamp the entire package. It is thoroughly tested and supports many features, such as supplementary row/columns, as well as row/column weights. Example usage This chart is interactive, which doesn't show on GitHub. The green points are the column loadings. Installation 🎨 Prince uses Altair for making charts. Methods 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) Principal geodesic analysis (PGA) Correctness Prince is tested against scikit-learn and FactoMineR. For the latter, rpy2 is used to run code in R, and convert the results to Python, which allows running automated tests. PGA is tested against geomstats. See more in the tests directory. Citation Please use this citation if you use this software as part of a scientific publication. License The MIT License (MIT). Please see the license file for more information.","default_branch":null,"files":null,"tree":[],"storefront":"/r/MaxHalford","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/MaxHalford/prince/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}