# Gallery

Every plot below is rendered live by reaborn in R from the seaborn-style code shown above it. Where it helps, a side-by-side panel shows the same plot in reaborn and in Python seaborn — they are designed to be indistinguishable.

## Reaborn vs. seaborn, at a glance

## Relational

### scatterplot

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

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

### lineplot

With per-group aggregation and a bootstrap confidence band — matching seaborn.

    lineplot(data = fmri, x = "timepoint", y = "signal", hue = "event")

### relplot

A figure-level wrapper that facets across `col`/`row`.

    relplot(data = fmri, x = "timepoint", y = "signal", hue = "event",
            col = "region", kind = "line")

## Distributions

### histplot

    histplot(data = penguins, x = "flipper_length_mm", hue = "species", multiple = "stack")

### kdeplot

The KDE reproduces `scipy.stats.gaussian_kde` to machine precision.

    kdeplot(data = penguins, x = "flipper_length_mm", hue = "species", fill = TRUE)

### ecdfplot

    ecdfplot(data = penguins, x = "bill_length_mm", hue = "species")

### displot

    displot(data = penguins, x = "flipper_length_mm", col = "species")

## Categorical

### boxplot & violinplot

    boxplot(data = tips, x = "day", y = "total_bill", hue = "smoker")

    violinplot(data = tips, x = "day", y = "total_bill")

### boxenplot

A faithful letter-value plot for larger samples.

    boxenplot(data = penguins, x = "species", y = "body_mass_g")

### stripplot & swarmplot

    stripplot(data = tips, x = "day", y = "total_bill", hue = "sex")

    swarmplot(data = tips, x = "day", y = "total_bill")

### barplot & pointplot

Error bars are seaborn’s bootstrap CI, not an analytic standard error.

    barplot(data = tips, x = "day", y = "total_bill")

    pointplot(data = tips, x = "day", y = "total_bill", hue = "sex")

## Regression

### regplot

The confidence band is a bootstrap interval, like seaborn.

    regplot(data = tips, x = "total_bill", y = "tip")

### lmplot

    lmplot(data = tips, x = "total_bill", y = "tip", col = "time", hue = "smoker")

## Matrix

### heatmap

    flights <- load_dataset("flights")
    mat <- tapply(flights$passengers, list(flights$month, flights$year), function(x) x[1])
    heatmap(mat, annot = TRUE, fmt = "d", linewidths = 0.5)

### clustermap

    clustermap(mat)

## Multi-plot grids

### jointplot

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

### pairplot

    pairplot(penguins, vars = c("bill_length_mm", "bill_depth_mm", "flipper_length_mm"),
             hue = "species")

## Palettes & themes

reaborn ships seaborn’s palettes, matched to the hex digit, and its five styles.

    palplot(color_palette("deep"))

    palplot(color_palette("husl", 8))

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

    set_theme()  # restore the default darkgrid