Building a violin plot with
ggplot2 is pretty straightforward thanks to the dedicated
geom_violin() function. Here, calling
coord_flip() allows to flip X and Y axis and thus get a
horizontal version of the chart. Moreover, note the use of the
theme_ipsum of the hrbrthemes library that
improves general appearance.
# Libraries
library(ggplot2)
library(dplyr)
library(tidyr)
library(forcats)
library(hrbrthemes)
library(viridis)
# Load dataset from github
data <- read.table("https://raw.githubusercontent.com/zonination/perceptions/master/probly.csv", header=TRUE, sep=",")
# Data is at wide format, we need to make it 'tidy' or 'long'
data <- data %>%
gather(key="text", value="value") %>%
mutate(text = gsub("\\.", " ",text)) %>%
mutate(value = round(as.numeric(value),0)) %>%
filter(text %in% c("Almost Certainly","Very Good Chance","We Believe","Likely","About Even", "Little Chance", "Chances Are Slight", "Almost No Chance"))
# Plot
p <- data %>%
mutate(text = fct_reorder(text, value)) %>% # Reorder data
ggplot( aes(x=text, y=value, fill=text, color=text)) +
geom_violin(width=2.1, size=0.2) +
scale_fill_viridis(discrete=TRUE) +
scale_color_viridis(discrete=TRUE) +
theme_ipsum() +
theme(
legend.position="none"
) +
coord_flip() + # This switch X and Y axis and allows to get the horizontal version
xlab("") +
ylab("Assigned Probability (%)")
p
