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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:

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

BSD 3-Clause (matching seaborn). seaborn is © Michael Waskom.