tinyplot

tinyplot is a lightweight extension of the base R graphics system. It is designed to bridge the gap between the powerful infrastructure of base R (like the plot() generic and formula-based interfaces) and the convenience features found in grid-based packages like ggplot2 or lattice.

Key features include:

• Preservation of the base R formula-based interface (y ~ x).
• Support for grouped plots with automatic legends and facets.
• Advanced visualization types.
• Easy customization via ready-made themes.
• Minimal non-base dependencies.

tinyplot is available on CRAN. You can install it using the standard R installation commands.

install.packages("tinyplot")

You can install the stable version of tinyplot from CRAN or the latest development version from R-universe.

From CRAN:

install.packages("tinyplot")

From R-universe (development version):

install.packages("tinyplot", repos = "https://grantmcdermott.r-universe.dev")

tinyplot is a lightweight extension of the base R graphics system. It is designed to be a drop-in replacement for the standard plot() function while adding convenience features like:

• Automatic grouping and legends
• Faceting (displaying groups in separate plots)
• Built-in themes
• Support for various plot types (e.g., density plots, linear models)

It has zero recursive dependencies and maintains a minimal footprint, making it suitable for package developers who want sophisticated plots without heavy dependencies.

The core function tinyplot() (or its shorthand alias plt()) allows you to create plots using formula syntax. It supports grouping via the | operator in formulas and automatic legend generation.

Grouped scatterplot using formula syntax:

tinyplot(Sepal.Length ~ Petal.Length | Species, data = iris)

Grouped scatterplot using the plt() shorthand with aesthetic tweaks:

plt(
  Sepal.Length ~ Petal.Length | Species, 
  data = iris,
  palette = "dark", pch = 16,
  grid = TRUE, frame = FALSE
)

tinyplot supports faceting and continuous color gradients for grouping.

plt(
  Sepal.Length ~ Petal.Length | Sepal.Length, data = iris,
  facet = ~Species, pch = 19,
  main = "Faceted flowers", sub = "Brought to you by tinyplot"
)

You can create density plots with automatic grouping and filling using the type = "density" and fill = "by" arguments.

plt(
  ~ Petal.Length | Species,
  data = iris,
  type = "density",
  fill = "by",
  main = "Distribution of petal lengths",
  sub = "Grouped by species"
)

After creating a plot with plt(), you can add layers or statistical transformations using plt_add().

Example: Adding a linear model (lm) layer:

plt(Sepal.Length ~ Petal.Length | Species, data = iris)
plt_add(type = "lm")

tinyplot provides built-in themes for convenient customization. Themes are persistent and will be applied to all subsequent plots until changed or reset.

Set a theme:

tinytheme("clean2")

Reset to default theme:

tinytheme()