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reaborn

reaborn is an R port of Python’s seaborn. It mirrors seaborn’s public function API — identical function names, argument names, and defaults — and renders visually indistinguishable plots using ggplot2. You can paste seaborn Python into R and get the same plot.

Because every reaborn plot is a ggplot, you can extend it with the entire ggplot2 grammar of graphics — something seaborn can’t do.

install.packages("reaborn")
library(reaborn)

Or install the development version from GitHub:

# install.packages("remotes")
remotes::install_github("shawntz/reaborn")

Paste seaborn Python into R

library(reaborn) installs the seaborn default theme and palette globally (like sns.set_theme()), exposes sns.-prefixed aliases for every function, and binds the Python literals True/False/None. So this seaborn snippet runs verbatim:

penguins <- load_dataset("penguins")

sns.scatterplot(data = penguins, x = "bill_length_mm", y = "bill_depth_mm",
                hue = "species")

sns.histplot(data = penguins, x = "flipper_length_mm", hue = "species",
             multiple = "stack", kde = True)

Or write it idiomatically (the sns. prefix is optional):

scatterplot(data = penguins, x = "bill_length_mm", y = "bill_depth_mm", hue = "species")

reaborn plots are ggplots

Every function returns a ggplot, so compose freely:

scatterplot(data = penguins, x = "bill_length_mm", y = "bill_depth_mm", hue = "species") +
  ggplot2::facet_wrap(~island) +
  ggplot2::scale_x_log10() +
  ggplot2::labs(title = "Penguin bills")

What’s implemented

The full classic seaborn function API:

Module	Functions
Relational	`scatterplot` `lineplot` `relplot`
Distributions	`histplot` `kdeplot` `ecdfplot` `rugplot` `displot`
Categorical	`boxplot` `violinplot` `boxenplot` `stripplot` `swarmplot` `barplot` `pointplot` `countplot` `catplot`
Regression	`regplot` `residplot` `lmplot`
Matrix	`heatmap` `clustermap`
Grids	`pairplot` `jointplot` `FacetGrid`
Misc	`palplot` `dogplot`
Palettes	`color_palette` `hls_palette` `husl_palette` `cubehelix_palette` `light_palette` `dark_palette` `diverging_palette` `blend_palette` `mpl_palette` `set_color_codes` …
Theming	`set_theme` `set_style` `set_context` `axes_style` `plotting_context` `despine` `move_legend` …

Fidelity

reaborn matches seaborn by extracting ground-truth constants from a real seaborn install rather than approximating:

Palettes match seaborn’s hex codes exactly.
Themes reproduce the five seaborn styles × four contexts.

Python → R conversion notes

Most seaborn calls paste over directly. The remaining edits are language-level:

Python	R
`sns.scatterplot(...)`	works as-is (`sns.scatterplot`)
`data=df, x="col", hue="g"`	works as-is (named args, string columns)
`True` / `False` / `None`	bound for you, or write `TRUE` / `FALSE` / `NULL`
`[1, 2, 3]` (list)	`c(1, 2, 3)`
`{"a": 1}` (dict)	`list(a = 1)`
`(1, 2)` (tuple)	`c(1, 2)`
`df.col`	`df$col`

License

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