Violin Plots in ggplot2

How to make Violin Plots in ggplot2 with Plotly.

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Default violin plot

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin()

plotly::ggplotly(p)

Flip plot orientation

library(plotly)
library(ggplot2)

p <-   
 ggplot(mtcars, aes(mpg, factor(cyl))) +
  geom_violin()

plotly::ggplotly(p)

With geom_violin(), the y-axis must always be the continuous variable, and the x-axis the categorical variable. To create horizontal violin graphs, keep the x- and y-variables as is and add coord_flip().

library(plotly)
library(ggplot2)

district_density <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/district_density.csv", stringsAsFactors = FALSE)
district_density$cluster <- factor(district_density$cluster, levels=c("Pure urban", "Urban-suburban mix", "Dense suburban", "Sparse suburban", "Rural-suburban mix", "Pure rural"))
district_density$region <- factor(district_density$region, levels=c("West", "South", "Midwest", "Northeast"))

p <- ggplot(district_density,aes(x=cluster, y=dem_margin, fill=cluster)) +
  geom_violin(colour=NA) +
  geom_hline(yintercept=0, alpha=0.5) +
  labs(title = "Democratic performance in the 2018 House elections, by region and density",
       x = "Density Index\nfrom CityLab",
       y = "Margin of Victory/Defeat") +
  coord_flip()

ggplotly(p)

Add data points with jitter

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin() + geom_jitter(height = 0, width = 0.1)

plotly::ggplotly(p)

Scaling maximum width

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin(scale = "count")

plotly::ggplotly(p)

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin(scale = "width")

plotly::ggplotly(p)

Disabling default trim

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin(trim = FALSE)

plotly::ggplotly(p)

Closer density fit

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin(adjust = .5)

plotly::ggplotly(p)

Adding fill

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin(aes(fill = cyl))

plotly::ggplotly(p)

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin(aes(fill = factor(cyl)))

plotly::ggplotly(p)

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin(aes(fill = factor(vs)))

plotly::ggplotly(p)

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin(aes(fill = factor(am)))

plotly::ggplotly(p)

Changing border colour

library(plotly)
library(ggplot2)

p <- ggplot(mtcars, aes(factor(cyl), mpg))
p <- p + geom_violin(fill = "grey80", colour = "#3366FF")

plotly::ggplotly(p)