This is an opinionated essay about good and bad practices in data visualization. Examples and explanations are below. The Scripts/ directory contains .Rmd files that generate the graphics shown below.

{colourpicker} gives you a colour picker widget that can be used in different contexts in R. You can use colourInput() to include a colour picker input in Shiny apps (or in R markdown documents). It ...

For everything from styling text and customizing color palettes to creating your own geoms, these ggplot2 add-ons deserve a place in your R data visualization toolkit. Plus, a bonus list of packages ...

Learn how to make the most of Observable JavaScript and the Observable Plot library, including a step-by-step guide to eight basic data visualization tasks in Plot. Built-in reactivity is one of ...

Alluvial diagrams use stacked bar plots and variable-width ribbons to represent multi-dimensional or repeated-measures data comprising categorical or ordinal variables (Bojanowski & Edwards, 2016; ...

Monomethylation on lysine 4 of histone H3 (H3K4me1) is commonly associated with distal enhancers, but H3K4me1 is also present at promoter regions proximal to transcription start sites. To assess a ...

Single-cell RNA-seq (scRNA-seq) allows researchers to define cell types on the basis of unsupervised clustering of the transcriptome. However, differences in experimental methods and computational ...

Effect sizes are the most important outcome of empirical studies. Most articles on effect sizes highlight their importance to communicate the practical significance of results. For scientists ...