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 ...

Idiopathic pulmonary fibrosis (IPF) is a fatal disease of unknown etiology with a poor prognosis, characterized by a lack of effective diagnostic and therapeutic interventions. The role of immunity in ...

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 ...

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 ...