Package 'reaborn'

Title: Statistical Data Visualization, the 'seaborn' Way
Description: An 'R' port of the 'Python' 'seaborn' library. 'reaborn' mirrors the 'seaborn' public function API (identical function names, argument names, and defaults) and renders visually indistinguishable plots using 'ggplot2'. Because every 'reaborn' plot is a 'ggplot' object, it can be extended with the full 'ggplot2' grammar of graphics.
Authors: Shawn Schwartz [aut, cre] (ORCID: <https://orcid.org/0000-0001-6444-8451>)
Maintainer: Shawn Schwartz <[email protected]>
License: BSD_3_clause + file LICENSE
Version: 1.0.0
Built: 2026-07-01 11:12:28 UTC
Source: https://github.com/shawntz/reaborn

Help Index

Get the parameters that control the general style of the plots

Description

Port of seaborn.axes_style. Returns the resolved style definition.

Usage

axes_style(style = NULL, rc = NULL)

set_style(style = NULL, rc = NULL)

Arguments

style

One of "darkgrid", "whitegrid", "dark", "white", "ticks".
rc

Optional named list of overrides.

Value

A named list describing the style.

Show point estimates and errors as bars

Description

Port of seaborn.barplot. Bar heights are an aggregate (default mean) with a bootstrap CI error bar. Returns a reaborn_plot.

Usage

barplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  order = NULL,
  hue_order = NULL,
  estimator = "mean",
  errorbar = list("ci", 95),
  n_boot = 1000,
  seed = NULL,
  units = NULL,
  weights = NULL,
  orient = NULL,
  color = NULL,
  palette = NULL,
  saturation = 0.75,
  fill = TRUE,
  width = 0.8,
  dodge = "auto",
  gap = 0,
  capsize = 0,
  err_kws = NULL,
  legend = "auto",
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables; the categorical one defines the groups.
hue

Grouping variable for color (dodged).
order, hue_order

Level orderings.
estimator, errorbar, n_boot, seed

Aggregation + error settings.
units, weights

Bootstrap structure / weights (units reserved).
orient

"v", "h", or NULL to infer.
color, palette, saturation, fill

Color controls (saturation default 0.75).
width, gap

Box width and gap between dodged boxes.
dodge

How to dodge bars by hue ("auto", TRUE, or FALSE).
capsize

Width of the error bar caps.
err_kws

Passed to the error bar geom.
legend

Legend control.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to the bar geom.

Value

A reaborn_plot.

Draw an enhanced box plot for larger datasets

Description

Port of seaborn.boxenplot (letter-value plot). Returns a reaborn_plot.

Usage

boxenplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  order = NULL,
  hue_order = NULL,
  orient = NULL,
  color = NULL,
  palette = NULL,
  saturation = 0.75,
  fill = TRUE,
  width = 0.8,
  gap = 0,
  linewidth = NULL,
  linecolor = NULL,
  width_method = "exponential",
  k_depth = "tukey",
  outlier_prop = 0.007,
  trust_alpha = 0.05,
  showfliers = TRUE,
  legend = "auto",
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables; the categorical one defines the groups.
hue

Grouping variable for color (dodged).
order, hue_order

Level orderings.
orient

"v", "h", or NULL to infer.
color, palette, saturation, fill

Color controls (saturation default 0.75).
width, gap

Box width and gap between dodged boxes.
linewidth

Box outline width.
linecolor

Box outline color.
width_method

"exponential", "linear", or "area".
k_depth

"tukey", "proportion", "trustworthy", "full", or an int.
outlier_prop, trust_alpha

Tail-rule parameters.
showfliers

Draw outlier points.
legend

Legend control.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to ggplot2::geom_boxplot.

Value

A reaborn_plot.

Draw a box plot

Description

Port of seaborn.boxplot. Returns a reaborn_plot.

Usage

boxplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  order = NULL,
  hue_order = NULL,
  orient = NULL,
  color = NULL,
  palette = NULL,
  saturation = 0.75,
  fill = TRUE,
  dodge = "auto",
  width = 0.8,
  gap = 0,
  whis = 1.5,
  linecolor = "auto",
  linewidth = NULL,
  fliersize = NULL,
  legend = "auto",
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables; the categorical one defines the groups.
hue

Grouping variable for color (dodged).
order, hue_order

Level orderings.
orient

"v", "h", or NULL to infer.
color, palette, saturation, fill

Color controls (saturation default 0.75).
dodge

How to dodge boxes by hue ("auto", TRUE, or FALSE).
width, gap

Box width and gap between dodged boxes.
whis

Whisker length in IQR units (default 1.5).
linecolor, linewidth, fliersize

Line and outlier styling.
legend

Legend control.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to ggplot2::geom_boxplot.

Value

A reaborn_plot.

Figure-level interface for categorical plots

Description

Port of seaborn.catplot. Dispatches to stripplot (kind = "strip"), boxplot, barplot, pointplot, or countplot and adds row/col faceting. Returns a faceted reaborn_plot.

Usage

catplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  row = NULL,
  col = NULL,
  kind = "strip",
  estimator = "mean",
  errorbar = list("ci", 95),
  n_boot = 1000,
  seed = NULL,
  units = NULL,
  weights = NULL,
  order = NULL,
  hue_order = NULL,
  row_order = NULL,
  col_order = NULL,
  col_wrap = NULL,
  height = 5,
  aspect = 1,
  orient = NULL,
  color = NULL,
  palette = NULL,
  legend = "auto",
  facet_kws = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables; the categorical one defines the groups.
hue

Grouping variable for color (dodged).
row, col, col_wrap, row_order, col_order

Faceting controls.
kind

One of "strip", "box", "bar", "point", "count".
estimator, errorbar, n_boot, seed

Aggregation settings (bar/point).
units

Unit grouping for bootstrap (bar/point kinds).
weights

Observation weights (bar/point kinds).
order, hue_order

Level orderings.
height, aspect

Facet sizing (stored as attributes).
orient

"v", "h", or NULL to infer.
color

Single color override.
palette

Palette for the hue mapping.
legend

Legend control.
facet_kws

Reserved for compatibility.
...

Passed to the underlying plotter.

Value

A reaborn_plot.

Plot a hierarchically-clustered heatmap

Description

Port of seaborn.clustermap. Reorders rows/columns by hierarchical clustering and draws dendrograms alongside the heatmap. Returns a patchwork composition.

Usage

clustermap(
  data,
  method = "average",
  metric = "euclidean",
  z_score = NULL,
  standard_scale = NULL,
  row_cluster = TRUE,
  col_cluster = TRUE,
  cmap = NULL,
  dendrogram_ratio = 0.2,
  ...
)

Arguments

data

A matrix or data frame.
method

Linkage method (default "average").
metric

Distance metric (default "euclidean").
z_score

Normalize rows (0) or columns (1) to z-scores.
standard_scale

Scale rows (0) or columns (1) to ⁠[0, 1]⁠.
row_cluster, col_cluster

Whether to cluster rows / columns.
cmap

Colormap (default "rocket").
dendrogram_ratio

Fraction of the figure used by the dendrograms.
...

Passed to heatmap.

Value

A reaborn_plot (patchwork).

Return a list of colors or a continuous colormap defining a palette

Description

Port of seaborn.color_palette. Possible palette values include the name of a seaborn palette (deep, muted, bright, pastel, dark, colorblind), a matplotlib colormap name, "husl"/"hls", a cubehelix shorthand ("ch:..."), "light:<color>", "dark:<color>", "blend:<c1>,<c2>", or a sequence of colors.

Usage

color_palette(palette = NULL, n_colors = NULL, desat = NULL, as_cmap = FALSE)

hls_palette(n_colors = 6, h = 0.01, l = 0.6, s = 0.65, as_cmap = FALSE)

husl_palette(n_colors = 6, h = 0.01, s = 0.9, l = 0.65, as_cmap = FALSE)

dark_palette(
  color,
  n_colors = 6,
  reverse = FALSE,
  as_cmap = FALSE,
  input = "rgb"
)

light_palette(
  color,
  n_colors = 6,
  reverse = FALSE,
  as_cmap = FALSE,
  input = "rgb"
)

diverging_palette(
  h_neg,
  h_pos,
  s = 75,
  l = 50,
  sep = 1,
  n = 6,
  center = "light",
  as_cmap = FALSE
)

blend_palette(colors, n_colors = 6, as_cmap = FALSE, input = "rgb")

mpl_palette(name, n_colors = 6, as_cmap = FALSE)

cubehelix_palette(
  n_colors = 6,
  start = 0,
  rot = 0.4,
  gamma = 1,
  hue = 0.8,
  light = 0.85,
  dark = 0.15,
  reverse = FALSE,
  as_cmap = FALSE
)

Arguments

palette

NULL, a string, or a sequence of colors.
n_colors

Number of colors. If NULL, depends on palette.
desat

Proportion to desaturate each color by.
as_cmap

If TRUE, return a continuous colormap (a reaborn_cmap).
h, l, s

Hue, lightness, saturation anchors in ⁠[0, 1]⁠.
color

Base color for the high end of a sequential palette.
reverse

Reverse the direction of the blend.
input

Color space of the input color: "rgb", "hls", or "husl".
h_neg, h_pos

Anchor hues (⁠[0, 359]⁠) for the negative and positive ends.
sep

Size of the intermediate (center) region.
n

Number of colors (when not returning a cmap).
center

"light" or "dark" center.
colors

A sequence of colors to blend between.
name

Name of a matplotlib colormap.
start, rot, gamma, hue, light, dark

Cubehelix parameters (see seaborn).

Value

A character vector of hex colors, or a reaborn_cmap.

Show value counts as bars

Description

Port of seaborn.countplot. Returns a reaborn_plot.

Usage

countplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  order = NULL,
  hue_order = NULL,
  orient = NULL,
  color = NULL,
  palette = NULL,
  saturation = 0.75,
  fill = TRUE,
  stat = "count",
  width = 0.8,
  dodge = "auto",
  gap = 0,
  legend = "auto",
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables; the categorical one defines the groups.
hue

Grouping variable for color (dodged).
order, hue_order

Level orderings.
orient

"v", "h", or NULL to infer.
color, palette, saturation, fill

Color controls (saturation default 0.75).
stat

"count", "percent", "proportion", or "probability".
width, gap

Box width and gap between dodged boxes.
dodge

How to dodge bars by hue ("auto", TRUE, or FALSE).
legend

Legend control.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to the bar geom.

Value

A reaborn_plot.

Decrease the saturation of a color

Description

Port of seaborn.desaturate.

Usage

desaturate(color, prop)

Arguments

color

A matplotlib-compatible color.
prop

Proportion (in ⁠[0, 1]⁠) of the original saturation to keep.

Value

A hex color string.

Remove spines from a plot

Description

Port of seaborn.despine. Returns a ggplot2 theme partial that removes the requested plot borders and (for borderless styles) draws explicit axis lines on the kept sides. Add it to a reaborn/ggplot plot: p + despine().

Usage

despine(
  fig = NULL,
  ax = NULL,
  top = TRUE,
  right = TRUE,
  left = FALSE,
  bottom = FALSE,
  offset = NULL,
  trim = FALSE
)

Arguments

fig, ax

Ignored (kept for signature compatibility with seaborn).
top, right, left, bottom

Logical; whether to remove that spine. Defaults match seaborn: remove top and right, keep left and bottom.
offset, trim

Not supported by ggplot2; accepted but ignored in v1 with a one-time message. Present for signature compatibility.

Value

A ggplot2 theme object to add to a plot.

Figure-level interface for distribution plots

Description

Port of seaborn.displot. Draws histplot (kind = "hist"), kdeplot (kind = "kde"), or ecdfplot (kind = "ecdf") onto a grid of facets. Returns a faceted reaborn_plot.

Usage

displot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  row = NULL,
  col = NULL,
  weights = NULL,
  kind = "hist",
  rug = FALSE,
  rug_kws = NULL,
  palette = NULL,
  hue_order = NULL,
  hue_norm = NULL,
  color = NULL,
  col_wrap = NULL,
  row_order = NULL,
  col_order = NULL,
  legend = TRUE,
  height = 5,
  aspect = 1,
  facet_kws = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Column name/vector for the histogram variable (use y for a horizontal histogram).
hue

Grouping variable for color.
row, col, col_wrap, row_order, col_order

Faceting controls.
weights

Optional observation weights.
kind

"hist", "kde", or "ecdf".
rug

Add a marginal rug.
rug_kws

Arguments forwarded to the rug layer when rug = TRUE.
palette, hue_order, hue_norm, color

Color controls.
legend

Show the legend.
height, aspect

Facet size controls (stored as attributes).
facet_kws

Reserved for compatibility.
...

Passed to the bar geom.

Value

A reaborn_plot.

Who's a good boy?

Description

Port of seaborn.dogplot (an easter egg). Prints an affirmation.

Usage

dogplot(...)

Arguments

...

Ignored.

Value

Invisibly NULL.

Plot an empirical cumulative distribution function

Description

Port of seaborn.ecdfplot. Returns a reaborn_plot.

Usage

ecdfplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  weights = NULL,
  stat = "proportion",
  complementary = FALSE,
  palette = NULL,
  hue_order = NULL,
  hue_norm = NULL,
  legend = TRUE,
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Column name/vector for the histogram variable (use y for a horizontal histogram).
hue

Grouping variable for color.
weights

Optional observation weights.
stat

"proportion", "count", or "percent".
complementary

Plot the complementary ECDF (1 - F).
palette

Palette for the hue mapping.
hue_order

Order of hue levels.
hue_norm

Normalization for a numeric hue.
legend

Show the legend.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to the bar geom.

Value

A reaborn_plot.

A faceted grid of plots

Description

Lightweight port of seaborn.FacetGrid. In reaborn, faceting is usually done by adding + ggplot2::facet_wrap()/facet_grid() to a plot, or via the figure-level functions (relplot, displot, catplot, lmplot). This constructor returns a base plot you can map geoms onto.

Usage

FacetGrid(
  data,
  row = NULL,
  col = NULL,
  hue = NULL,
  col_wrap = NULL,
  height = 3,
  aspect = 1,
  palette = NULL
)

Arguments

data

A data frame.
row, col, hue

Faceting / hue variables.
col_wrap

Wrap columns at this width.
height, aspect

Facet sizing.
palette

Hue palette.

Value

A reaborn_plot.

Plot rectangular data as a color-encoded matrix

Description

Port of seaborn.heatmap. Returns a reaborn_plot.

Usage

heatmap(
  data,
  vmin = NULL,
  vmax = NULL,
  cmap = NULL,
  center = NULL,
  robust = FALSE,
  annot = NULL,
  fmt = ".2g",
  annot_kws = NULL,
  linewidths = 0,
  linecolor = "white",
  cbar = TRUE,
  square = FALSE,
  xticklabels = "auto",
  yticklabels = "auto",
  mask = NULL,
  ...
)

Arguments

data

A matrix or data frame of values.
vmin, vmax

Color scale limits.
cmap

A colormap name (default "rocket", or "icefire" with center).
center

Value at which to center a diverging colormap.
robust

Use the 2nd/98th percentiles for the color limits.
annot

Annotate each cell with its value (TRUE) or a matrix of labels.
fmt

Number format for annotations (default ".2g").
annot_kws

Passed to the text geom.
linewidths, linecolor

Cell border width and color.
cbar

Show the color bar.
square

Force square cells.
xticklabels, yticklabels

Tick label control ("auto", TRUE/FALSE).
mask

Logical matrix of cells to hide.
...

Reserved.

Value

A reaborn_plot.

Plot a univariate or bivariate histogram

Description

Port of seaborn.histplot. Returns a reaborn_plot.

Usage

histplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  weights = NULL,
  stat = "count",
  bins = "auto",
  binwidth = NULL,
  binrange = NULL,
  discrete = NULL,
  cumulative = FALSE,
  common_bins = TRUE,
  common_norm = TRUE,
  multiple = "layer",
  element = "bars",
  fill = TRUE,
  shrink = 1,
  kde = FALSE,
  kde_kws = NULL,
  palette = NULL,
  hue_order = NULL,
  hue_norm = NULL,
  color = NULL,
  legend = TRUE,
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Column name/vector for the histogram variable (use y for a horizontal histogram).
hue

Grouping variable for color.
weights

Optional observation weights.
stat

One of "count", "frequency", "density", "probability", "proportion", "percent".
bins, binwidth, binrange, discrete

Binning controls (see rb_hist_bins).
cumulative

Accumulate counts.
common_bins, common_norm

Share bins/normalization across hue groups.
multiple

"layer", "stack", "fill", or "dodge".
element

"bars" or "step".
fill

Whether to fill the bars.
shrink

Shrink bar widths by this factor.
kde

Overlay a KDE curve.
kde_kws

Arguments for the KDE (e.g. bw_adjust).
palette, hue_order, hue_norm, color

Color controls.
legend

Show the legend.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to the bar geom.

Value

A reaborn_plot.

Draw a bivariate plot with marginal distributions

Description

Port of seaborn.jointplot. Returns a patchwork composition (printable and saveable like any reaborn plot).

Usage

jointplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  kind = "scatter",
  height = 6,
  ratio = 5,
  space = 0.2,
  color = NULL,
  palette = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables.
hue

Grouping variable for color.
kind

"scatter", "kde", "reg", "hist", or "hex".
height

Figure size in inches (stored as an attribute).
ratio

Joint-axes-to-marginal size ratio.
space

Spacing between joint and marginal axes.
color, palette

Color controls.
...

Passed to the joint plotting function.

Value

A reaborn_plot (patchwork).

Plot a univariate or bivariate kernel density estimate

Description

Port of seaborn.kdeplot. The KDE matches scipy.stats.gaussian_kde exactly. Returns a reaborn_plot.

Usage

kdeplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  weights = NULL,
  palette = NULL,
  hue_order = NULL,
  hue_norm = NULL,
  color = NULL,
  fill = NULL,
  multiple = "layer",
  common_norm = TRUE,
  common_grid = FALSE,
  cumulative = FALSE,
  bw_method = "scott",
  bw_adjust = 1,
  log_scale = NULL,
  levels = 10,
  thresh = 0.05,
  gridsize = 200,
  cut = 3,
  clip = NULL,
  legend = TRUE,
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Column name/vector for the histogram variable (use y for a horizontal histogram).
hue

Grouping variable for color.
weights

Optional observation weights.
palette, hue_order, hue_norm, color

Color controls.
fill

Fill under the density curve (default FALSE).
multiple

"layer", "stack", or "fill".
common_norm, common_grid

Share normalization / evaluation grid across hue groups.
cumulative

Plot the cumulative distribution.
bw_method, bw_adjust

Bandwidth controls (scipy-compatible).
log_scale

Reserved for compatibility.
levels, thresh

Bivariate contour levels and density threshold.
gridsize, cut, clip

KDE grid controls.
legend

Show the legend.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to the bar geom.

Value

A reaborn_plot.

Draw a line plot with aggregation and error bands

Description

Port of seaborn.lineplot. When the data has repeated observations per x value, they are aggregated (default: mean) and an error band (default: 95% bootstrap CI) is drawn. Returns a reaborn_plot.

Usage

lineplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  size = NULL,
  style = NULL,
  units = NULL,
  weights = NULL,
  palette = NULL,
  hue_order = NULL,
  hue_norm = NULL,
  sizes = NULL,
  size_order = NULL,
  size_norm = NULL,
  dashes = TRUE,
  markers = NULL,
  style_order = NULL,
  estimator = "mean",
  errorbar = list("ci", 95),
  n_boot = 1000,
  seed = NULL,
  orient = "x",
  sort = TRUE,
  err_style = "band",
  err_kws = NULL,
  legend = "auto",
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Column names (strings) or vectors giving the axes.
hue, size, style

Column names/vectors for color, size, and marker-style semantics.
units, weights

Column names/vectors for the unit grouping and weights.
palette, hue_order, hue_norm

Control the color mapping.
sizes, size_order, size_norm

Control the size mapping.
dashes, markers

Style mapping controls.
style_order

Order of style levels.
estimator

Aggregation function name or callable (default "mean"; NULL to plot all observations).
errorbar

Error representation: a method name or list(method, level) (default list("ci", 95)).
n_boot, seed

Bootstrap settings for errorbar = "ci".
orient, sort, err_style, err_kws

See seaborn.
legend

"auto", "brief", "full", or FALSE.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to ggplot2::geom_line.

Value

A reaborn_plot.

Figure-level interface for regression plots

Description

Port of seaborn.lmplot. Draws regplot across a grid of facets and/or hue groups. Returns a reaborn_plot.

Usage

lmplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  col = NULL,
  row = NULL,
  palette = NULL,
  col_wrap = NULL,
  height = 5,
  aspect = 1,
  order = 1,
  logistic = FALSE,
  lowess = FALSE,
  robust = FALSE,
  logx = FALSE,
  ci = 95,
  n_boot = 1000,
  seed = NULL,
  scatter = TRUE,
  fit_reg = TRUE,
  hue_order = NULL,
  row_order = NULL,
  col_order = NULL,
  legend = TRUE,
  facet_kws = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables.
hue, col, row

Semantic / faceting variables.
palette

Hue palette.
col_wrap, row_order, col_order, hue_order

Ordering / wrapping.
height, aspect

Facet sizing.
order

Polynomial order for the fit (default 1, linear).
logistic, lowess, robust, logx

Alternative fits.
ci

Confidence-band width (default 95; NULL to omit).
n_boot, seed

Bootstrap settings.
scatter, fit_reg

Whether to draw the scatter / the fit.
legend, facet_kws

Legend / facet options.
...

Reserved.

Value

A reaborn_plot.

Load an example dataset from the seaborn-data repository

Description

Port of seaborn.load_dataset. Bundled datasets (penguins, tips, iris, flights) load offline; others download from the seaborn-data repo and cache.

Usage

load_dataset(name, cache = TRUE, data_home = NULL, ...)

get_dataset_names()

Arguments

name

Name of the dataset (the stem of a .csv in seaborn-data).
cache

Whether to use the local cache (and bundled data).
data_home

Optional cache directory.
...

Reserved for compatibility.

Value

A data.frame, with categorical columns coerced to ordered factors matching seaborn.

For get_dataset_names, a character vector of available dataset names.

Reposition a plot's legend

Description

Port of seaborn.move_legend. Returns a theme partial controlling legend position. Add it to a plot: p + move_legend("upper right").

Usage

move_legend(obj = NULL, loc = "best", ...)

Arguments

obj

Ignored (signature compatibility).
loc

A seaborn/matplotlib location string (e.g. "upper right", "center left"), "best", or a length-2 numeric vector of relative coords.
...

Additional theme arguments (e.g. title).

Value

A ggplot2 theme object to add to a plot.

Plot pairwise relationships in a dataset

Description

Port of seaborn.pairplot. Returns a patchwork matrix of scatter plots with univariate distributions on the diagonal.

Usage

pairplot(
  data,
  vars = NULL,
  hue = NULL,
  kind = "scatter",
  diag_kind = "auto",
  palette = NULL,
  height = 2.5,
  aspect = 1,
  corner = FALSE,
  ...
)

Arguments

data

A data frame.
vars

Columns to include (default all numeric).
hue

Grouping variable for color.
kind

Off-diagonal kind: "scatter" or "reg".
diag_kind

Diagonal kind: "auto", "hist", or "kde".
palette, height, aspect, corner

Layout controls.
...

Reserved.

Value

A reaborn_plot (patchwork).

Plot the values in a color palette as a horizontal array

Description

Port of seaborn.palplot. Returns a reaborn_plot.

Usage

palplot(pal, size = 1)

Arguments

pal

A sequence of colors (e.g. from color_palette).
size

Scaling factor for the swatch size.

Value

A reaborn_plot.

Get the parameters that control the scaling of plot elements

Description

Port of seaborn.plotting_context. Returns a named list of resolved sizes.

Usage

plotting_context(context = NULL, font_scale = 1, rc = NULL)

set_context(context = NULL, font_scale = 1, rc = NULL)

Arguments

context

One of "paper", "notebook", "talk", "poster", or a list.
font_scale

Separate scaling factor applied to the font sizes only.
rc

Optional named list of overrides.

Value

A named list of context parameters.

Show point estimates and errors with markers

Description

Port of seaborn.pointplot. Returns a reaborn_plot.

Usage

pointplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  order = NULL,
  hue_order = NULL,
  estimator = "mean",
  errorbar = list("ci", 95),
  n_boot = 1000,
  seed = NULL,
  units = NULL,
  weights = NULL,
  color = NULL,
  palette = NULL,
  markers = "o",
  linestyles = "-",
  dodge = FALSE,
  orient = NULL,
  capsize = 0,
  legend = "auto",
  err_kws = NULL,
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables; the categorical one defines the groups.
hue

Grouping variable for color (dodged).
order, hue_order

Level orderings.
estimator, errorbar, n_boot, seed

Aggregation + error settings.
units, weights

Bootstrap structure / weights (units reserved).
color

Single color override.
palette

Palette for the hue mapping.
markers, linestyles

Marker and line styling.
dodge

Dodge points by hue.
orient

"v", "h", or NULL to infer.
capsize

Width of the error bar caps.
legend

Legend control.
err_kws

Passed to the error bar geom.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to the bar geom.

Value

A reaborn_plot.

Python literal compatibility values

Description

True, False, and None are provided so that seaborn Python code pasted into R (e.g. histplot(data = df, x = "a", kde = True)) runs unchanged. They are exactly TRUE, FALSE, and NULL.

Usage

True

False

None

Format

True and False are length-one logicals; None is NULL.

Value

These objects are exported constants, not functions. Referencing one yields its stored value: True is the length-one logical vector TRUE, False is the length-one logical vector FALSE, and None is NULL. They exist only so that seaborn code containing Python's True, False, and None literals evaluates in R unchanged.

Plot data and a linear regression model fit

Description

Port of seaborn.regplot. The confidence band is a bootstrap interval, like seaborn. Returns a reaborn_plot.

Usage

regplot(
  data = NULL,
  x = NULL,
  y = NULL,
  order = 1,
  logistic = FALSE,
  lowess = FALSE,
  robust = FALSE,
  logx = FALSE,
  ci = 95,
  n_boot = 1000,
  seed = NULL,
  scatter = TRUE,
  fit_reg = TRUE,
  color = NULL,
  marker = "o",
  scatter_kws = NULL,
  line_kws = NULL,
  truncate = TRUE,
  x_jitter = NULL,
  y_jitter = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables.
order

Polynomial order for the fit (default 1, linear).
logistic, lowess, robust, logx

Alternative fits.
ci

Confidence-band width (default 95; NULL to omit).
n_boot, seed

Bootstrap settings.
scatter, fit_reg

Whether to draw the scatter / the fit.
color

Color for points and line (default the first palette color).
marker

Marker (accepted for compatibility).
scatter_kws, line_kws

Lists of extra args for the point / line layers.
truncate

Limit the regression line to the data range.
x_jitter

Uniform jitter added to x for display only.
y_jitter

Uniform jitter added to y for display only.
...

Reserved.

Value

A reaborn_plot.

Figure-level interface for relational plots

Description

Port of seaborn.relplot. Draws scatterplot (kind = "scatter") or lineplot (kind = "line") onto a grid of facets defined by row/col. Returns a reaborn_plot (a faceted ggplot) with the legend outside, like a seaborn FacetGrid.

Usage

relplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  size = NULL,
  style = NULL,
  units = NULL,
  weights = NULL,
  row = NULL,
  col = NULL,
  col_wrap = NULL,
  row_order = NULL,
  col_order = NULL,
  palette = NULL,
  hue_order = NULL,
  hue_norm = NULL,
  sizes = NULL,
  size_order = NULL,
  size_norm = NULL,
  markers = NULL,
  dashes = NULL,
  style_order = NULL,
  legend = "auto",
  kind = "scatter",
  height = 5,
  aspect = 1,
  facet_kws = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Column names (strings) or vectors giving the axes.
hue, size, style

Column names/vectors for color, size, and marker-style semantics.
units, weights

Column names/vectors for the unit grouping and weights.
row, col

Column names to facet by.
col_wrap

Wrap the column facets at this width.
row_order, col_order

Facet orderings.
palette, hue_order, hue_norm

Control the color mapping.
sizes, size_order, size_norm

Control the size mapping.
dashes, markers

Style mapping controls.
style_order

Order of style levels.
legend

"auto", "brief", "full", or FALSE.
kind

"scatter" or "line".
height, aspect

Facet height (inches) and aspect ratio (stored as attributes used as defaults when saving).
facet_kws

Reserved for compatibility.
...

Passed to ggplot2::geom_line.

Value

A reaborn_plot.

Restore matplotlib/ggplot2 defaults

Description

Port of seaborn.reset_defaults / seaborn.reset_orig.

Usage

reset_defaults()

reset_orig()

Value

Invisibly NULL.

Plot the residuals of a linear regression

Description

Port of seaborn.residplot. Returns a reaborn_plot.

Usage

residplot(
  data = NULL,
  x = NULL,
  y = NULL,
  lowess = FALSE,
  order = 1,
  robust = FALSE,
  color = NULL,
  scatter_kws = NULL,
  line_kws = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables.
lowess

Add a lowess smooth of the residuals.
order

Polynomial order for the fit (default 1, linear).
robust

Fit a robust regression when computing residuals.
color

Color for points and line (default the first palette color).
scatter_kws, line_kws

Lists of extra args for the point / line layers.
...

Reserved.

Value

A reaborn_plot.

Plot marginal rug ticks

Description

Port of seaborn.rugplot. Draws small ticks at each observation along the relevant axis. Returns a reaborn_plot (typically added to another plot, but usable standalone).

Usage

rugplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  height = 0.025,
  expand_margins = TRUE,
  palette = NULL,
  hue_order = NULL,
  hue_norm = NULL,
  legend = TRUE,
  ...
)

Arguments

data

A data frame.
x, y

Column name/vector for the histogram variable (use y for a horizontal histogram).
hue

Grouping variable for color.
height

Tick height as a fraction of the axis (default 0.025).
expand_margins

Reserved for compatibility.
palette

Palette for the hue mapping.
hue_order

Order of hue levels.
hue_norm

Normalization for a numeric hue.
legend

Show the legend.
...

Passed to the bar geom.

Value

A reaborn_plot.

Increase the saturation of a color to its maximum

Description

Port of seaborn.saturate.

Usage

saturate(color)

Arguments

color

A matplotlib-compatible color.

Value

A hex color string.

Draw a scatter plot with semantic mappings

Description

Port of seaborn.scatterplot. Returns a reaborn_plot (a ggplot), so it can be extended with any ggplot2 component.

Usage

scatterplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  size = NULL,
  style = NULL,
  palette = NULL,
  hue_order = NULL,
  hue_norm = NULL,
  sizes = NULL,
  size_order = NULL,
  size_norm = NULL,
  markers = TRUE,
  style_order = NULL,
  legend = "auto",
  ...
)

Arguments

data

A data frame.
x, y

Column names (strings) or vectors giving the axes.
hue, size, style

Column names/vectors for color, size, and marker-style semantics.
palette, hue_order, hue_norm

Control the color mapping.
sizes, size_order, size_norm

Control the size mapping.
markers, style_order

Control the style (marker) mapping.
legend

"auto", "brief", "full", or FALSE.
...

Passed to ggplot2::geom_point.

Value

A reaborn_plot.

Change how single-letter color codes are interpreted

Description

Port of seaborn.set_color_codes. Returns (invisibly) the mapping from the single-letter codes ⁠b g r m y c k⁠ to the colors of the given seaborn palette, so reaborn helpers can resolve them like seaborn does.

Usage

set_color_codes(palette = "deep")

Arguments

palette

One of "deep", "muted", "pastel", "bright", "dark", "colorblind".

Value

Invisibly, the named character vector of code -> hex mappings.

Independently set the hue, lightness, and/or saturation of a color

Description

Port of seaborn.set_hls_values.

Usage

set_hls_values(color, h = NULL, l = NULL, s = NULL)

Arguments

color

A matplotlib-compatible color.
h, l, s

New hue, lightness, saturation in ⁠[0, 1]⁠, or NULL to keep.

Value

A hex color string.

Set the matplotlib color cycle / ggplot default discrete palette

Description

Port of seaborn.set_palette.

Usage

set_palette(palette, n_colors = NULL, desat = NULL, color_codes = FALSE)

Arguments

palette

A palette name or sequence (see color_palette).
n_colors, desat, color_codes

See seaborn.

Value

Invisibly NULL.

Set multiple theme parameters in one step

Description

Port of seaborn.set_theme (and its alias set). Sets the global look used by subsequent reaborn (and ggplot2) plots.

Usage

set_theme(
  context = "notebook",
  style = "darkgrid",
  palette = "deep",
  font = "sans",
  font_scale = 1,
  color_codes = TRUE,
  rc = NULL
)

set(...)

Arguments

context, style, palette, font, font_scale, color_codes, rc

See seaborn.
...

Passed to set_theme.

Value

Invisibly, the applied ggplot2::theme.

seaborn-style sns. function aliases

Description

For copy-paste compatibility with Python, reaborn provides a sns.-prefixed alias for every public plotting, palette, and theming function (R allows dots in identifiers). So pasted seaborn code such as sns.scatterplot(data = df, x = "a", y = "b", hue = "g") runs verbatim. Each alias is identical to its unprefixed counterpart; see that function for arguments and details.

Value

Each sns.-prefixed object is the exact same function as its unprefixed counterpart (sns.scatterplot <- scatterplot, and so on), so calling an alias returns precisely what the counterpart returns. By category: the plotting functions (e.g. sns.scatterplot(), sns.histplot(), sns.heatmap(), sns.pairplot(), sns.FacetGrid(), sns.palplot()) return a reaborn_plot object (a ggplot2/patchwork object that draws when printed), except the easter-egg sns.dogplot(), which prints an affirmation and returns NULL invisibly; the palette constructors (e.g. sns.color_palette(), sns.husl_palette(), sns.cubehelix_palette()) return a character vector of hex colors, or a reaborn_cmap; the color helpers sns.desaturate(), sns.saturate(), and sns.set_hls_values() return a hex color string; sns.axes_style() and sns.plotting_context() return a named list of style/context parameters; sns.despine() and sns.move_legend() return a ggplot2 theme object to add to a plot; sns.load_dataset() returns a data frame and sns.get_dataset_names() a character vector; and the theming setters (sns.set_theme(), sns.set(), sns.set_style(), sns.set_context(), sns.set_palette(), sns.set_color_codes(), sns.reset_defaults(), sns.reset_orig()) are called for their side effect of changing global plot defaults and return their value invisibly. See each unprefixed function's own help page for the precise structure and meaning of its return value.

Examples

pen <- load_dataset("penguins")
p <- sns.scatterplot(data = pen, x = "bill_length_mm", y = "bill_depth_mm",
                     hue = "species")

Draw a categorical scatter with jitter

Description

Port of seaborn.stripplot. Returns a reaborn_plot.

Usage

stripplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  order = NULL,
  hue_order = NULL,
  jitter = TRUE,
  dodge = FALSE,
  orient = NULL,
  color = NULL,
  palette = NULL,
  size = 5,
  edgecolor = "gray",
  linewidth = 0,
  legend = "auto",
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables; the categorical one defines the groups.
hue

Grouping variable for color (dodged).
order, hue_order

Level orderings.
jitter

TRUE, FALSE, or a numeric jitter amount.
dodge

Separate hue levels along the categorical axis.
orient

"v", "h", or NULL to infer.
color

Single color override.
palette

Palette for the hue mapping.
size

Marker size (seaborn default 5).
edgecolor, linewidth

Marker edge styling.
legend

Legend control.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to the point geom.

Value

A reaborn_plot.

Draw a categorical scatter with non-overlapping points

Description

Port of seaborn.swarmplot, using a beeswarm layout. Returns a reaborn_plot.

Usage

swarmplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  order = NULL,
  hue_order = NULL,
  dodge = FALSE,
  orient = NULL,
  color = NULL,
  palette = NULL,
  size = 5,
  edgecolor = NULL,
  linewidth = 0,
  legend = "auto",
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables; the categorical one defines the groups.
hue

Grouping variable for color (dodged).
order, hue_order

Level orderings.
dodge

Separate hue levels along the categorical axis.
orient

"v", "h", or NULL to infer.
color

Single color override.
palette

Palette for the hue mapping.
size

Marker size (seaborn default 5).
edgecolor, linewidth

Marker edge styling.
legend

Legend control.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to ggbeeswarm::geom_beeswarm.

Value

A reaborn_plot.

Build a ggplot2 theme replicating a seaborn style + context

Description

Build a ggplot2 theme replicating a seaborn style + context

Usage

theme_seaborn(
  style = "darkgrid",
  context = "notebook",
  font_scale = 1,
  font = "sans"
)

Arguments

style

A seaborn style name (see axes_style).
context

A seaborn context name (see plotting_context).
font_scale

Font scaling factor.
font

Base font family.

Value

A complete ggplot2::theme object.

Draw a violin plot

Description

Port of seaborn.violinplot. The kernel density matches scipy.stats.gaussian_kde. Returns a reaborn_plot.

Usage

violinplot(
  data = NULL,
  x = NULL,
  y = NULL,
  hue = NULL,
  order = NULL,
  hue_order = NULL,
  orient = NULL,
  color = NULL,
  palette = NULL,
  saturation = 0.75,
  fill = TRUE,
  inner = "box",
  split = FALSE,
  width = 0.8,
  dodge = "auto",
  gap = 0,
  linewidth = NULL,
  linecolor = "auto",
  cut = 2,
  gridsize = 100,
  bw_method = "scott",
  bw_adjust = 1,
  density_norm = "area",
  common_norm = FALSE,
  legend = "auto",
  inner_kws = NULL,
  .facet_vars = NULL,
  ...
)

Arguments

data

A data frame.
x, y

Variables; the categorical one defines the groups.
hue

Grouping variable for color (dodged).
order, hue_order

Level orderings.
orient

"v", "h", or NULL to infer.
color, palette, saturation, fill

Color controls (saturation default 0.75).
inner

"box", "quart", "stick", "point", or NULL.
split

Draw split violins for two hue levels.
width, gap

Box width and gap between dodged boxes.
dodge

How to dodge violins by hue ("auto", TRUE, or FALSE).
linewidth

Outline width.
linecolor

Outline color ("auto" for seaborn's gray).
cut, gridsize, bw_method, bw_adjust

KDE controls.
density_norm

"area", "count", or "width".
common_norm

Normalize densities across all groups together.
legend

Legend control.
inner_kws

Passed to the inner annotation geoms.
.facet_vars

Internal; facet columns forwarded by the figure-level dispatchers (catplot/displot/relplot). Not intended for direct use.
...

Passed to ggplot2::geom_boxplot.

Value

A reaborn_plot.