vizier

An R Package for Visualization of 2D Datasets.

Visualizing datasets in 2D (e.g. via PCA, Sammon Mapping, t-SNE) is much more informative if the points are colored, using something like:

• Factor levels mapped to different colors.
• A numeric value mapped to a color scale.
• A string encoding a color.

This package is to make doing that a bit easier, using the graphics::plot function, a returned ggplot2 object, or the plotly JavaScript library. If you don’t specify a specific column to color by, it will attempt to find a suitable factor or color column automatically, using the last suitable column found, so you can add a custom column to a dataframe if needed and have it picked out automatically.

Installing

install.packages("pak")
pak::pak("jlmelville/vizier")

Documentation

?embed_plot
?embed_ggplot
?embed_plotly

The pkgdown site has longer guides:

• Getting started
• Color schemes

Example

Create a plot of the first two principal components (PCA) for the iris dataset:

pca_iris <- stats::prcomp(iris[, -5], retx = TRUE, rank. = 2)

Simplest use of embed_plot: pass in data frame and it will use the last (in this case, only) factor column it finds and the stable built-in Polychrome 36 categorical palette.

embed_plot(pca_iris$x, iris)

Default embed plot result

For more examples, see the Getting started article.

License

GPL (>= 3). The code for the turbo color scheme is from https://gist.github.com/jlmelville/be981e2f36485d8ef9616aef60fd52ab and is licensed under Apache 2.

See Also

• More example datasets that I’ve used these functions with can be found in the snedata package.
• quadra for assessing the results quantitatively.