Principal Component Analysis Python Packages

pca

pca: A Python Package for Principal Component Analysis.

abess

Fast Best-Subset Selection Library

pyspm

Python library to handle Scanning Probe Microscopy Images. Can read nanoscan .xml data, Bruker AFM images, Nanonis SXM files as well as iontof images(ITA, ITM and ITS).

snpio

SNPio is a Python API for population genetic file processing, filtering, and analysis. It is designed to be a user-friendly tool for the manipulation of population genetic data in a variety of formats. SNPio can be used to filter data based on missingness, MAF and MAC, singletons, biallelic, and monomorphic sites. It can also generate summary statistics for population genetic analyses.

torch-pca

Principal Component Anlaysis (PCA) in PyTorch.

cvmatrix

Computation of training set (X^T * W * X) and (X^T * W * Y) or (X^T * X) and (X^T * Y) in a cross-validation setting using the fast algorithms by Engstrøm and Jensen (2025).

augmented-pca

Python implementations of supervised and adversarial linear factor models.

hoggorm

Explorative multivariate statistics in Python

xmca

Maximum Covariance Analysis in Python

ristretto

Randomized Dimension Reduction Library

ccsf

Leveraging cell-cell similarity from gene expression data for high-performance spatial and temporal cellular mappings.

divbrowse

A web application for interactive visualization and analysis of genotypic variant matrices

pydatafitting

package for specialized regression

rfflearn

Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model

nystrompca

Efficient non-linear PCA through kernel PCA with the Nyström method

synthia

📈 🐍 Multidimensional synthetic data generation with Copula and fPCA models in Python

delayedsparse

Efficient sparse matrix implementation for various "Principal Component Analysis"