Package: ggpca 0.1.4

ggpca: Publication-Ready PCA, t-SNE, and UMAP Plots

Provides tools for creating publication-ready dimensionality reduction plots, including Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP). This package helps visualize high-dimensional data with options for custom labels, density plots, and faceting, using the 'ggplot2' framework Wickham (2016) <doi:10.1007/978-3-319-24277-4>.

Authors:Yaoxiang Li [cre, aut]

ggpca_0.1.4.tar.gz
ggpca_0.1.4.zip(r-4.7-any)ggpca_0.1.4.zip(r-4.6-any)ggpca_0.1.4.zip(r-4.5-any)
ggpca_0.1.4.tgz(r-4.6-any)ggpca_0.1.4.tgz(r-4.5-any)
ggpca_0.1.4.tar.gz(r-4.7-any)ggpca_0.1.4.tar.gz(r-4.6-any)
ggpca_0.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
ggpca/json (API)

# Install 'ggpca' in R:

install.packages('ggpca', repos = c('https://yaoxiangli.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yaoxiangli/ggpca/issues

Pkgdown/docs site:https://yaoxiangli.github.io

On CRAN:

data-visualization ggplot2 pca

2.90 score 4 stars 2 scripts 227 downloads 3 exports 42 dependencies

Last updated from:22a2ce4e29. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	198
source / vignettes	OK	230
linux-release-x86_64	OK	189
macos-release-arm64	OK	139
macos-oldrel-arm64	OK	113
windows-devel-x86_64	OK	93
windows-release-x86_64	OK	86
windows-oldrel-x86_64	OK	90
wasm-release	OK	131