reaborn vs. seaborn vs. ggplot2

Where reaborn fits

reaborn is a faithful R port of Python’s seaborn, built on ggplot2. It mirrors seaborn’s public API exactly — same function names, same argument names, same defaults — so the plotting code you already know runs in R with little to no translation. The defaults that make seaborn plots look good out of the box (the styles, the palettes, the spacing) come along for the ride, because reaborn reproduces them rather than approximating them.

reaborn vs seaborn KDE

The part seaborn can’t match: every reaborn plot is a ggplot object. A call like scatterplot(...) returns a ggplot, so you can keep building with the full grammar of graphics — add facet_wrap(), swap in scale_x_log10(), layer extra geoms, override the theme. You get seaborn’s defaults as a starting point and ggplot2’s composability as the ceiling.

Coming from seaborn?

In most cases you change nothing but the language host. After library(reaborn), the sns. aliases, the global theme, and the True/False/None literals are all in scope, so a seaborn snippet pasted into R runs as-is.

library(reaborn)   # sets seaborn theme + palette globally, like sns.set_theme()

# This is literally seaborn code — it runs verbatim in R:
sns.scatterplot(data = penguins, x = "bill_length_mm", y = "bill_depth_mm",
                hue = "species")
Python (seaborn) R (reaborn) Note
import seaborn as sns library(reaborn) Sets theme/palette globally, exposes sns. aliases
sns.set_theme() automatic on load
sns.scatterplot(data=df, x="a", y="b", hue="g") same line, verbatim sns. alias + = kwargs both work
True / False / None True / False / None Bound to TRUE / FALSE / NULL
string columns: x="col" x = "col" seaborn’s string-column API is preserved
ax.set(...) (matplotlib) + ggplot2::labs(...), + theme(...) You now get the ggplot grammar

Coming from ggplot2?

You already love the grammar of graphics. reaborn doesn’t ask you to give it up — it hands you seaborn’s defaults and statistics as a starting layer, returned as an ordinary ggplot that you keep building.