Adding jitters to the violin plot
The geom_plot() can be improved by plotting the violin plot with data points using random noise to the actual data points on the x-axis. These data points are referred to as the “jitters”. The geom_jitter() method in R is used to add a small amount of random variation to the location of each point.
Example: Adding jitters to the violin plot
R
library("ggplot2")# defining the columns of the data framedata_frame <- data.frame(col1=c(rep("A", 10) , rep("B", 12) , rep("C", 18)), col2=c( sample(2:5, 10 , replace=T) , sample(4:10, 12 , replace=T), sample(1:7, 18 , replace=T)))# plotting the data frameggplot(data_frame, aes(x = col1, y = col2, fill = col1)) + # adding violin plot geom_violin() + geom_jitter() |
Output:
Violinplot with Data Points in R
How To Make Violinplot with Data Points in R?
In this article, we will discuss how to make violinplot with data points in the R programming language.
A violin plot is a compact display of a continuous distribution. The geom_violin() method in R is used to construct a violin plot in the working space which understands various aesthetic mappings, like alpha, color or fill.
Syntax:
geom_violin()
To construct a regular violin plot simply call the geom_violin() function after the visualization.
Example: A regular violin plot.
R
library("ggplot2")# defining the columns of the data framedata_frame <- data.frame(col1=c(rep("A", 10) , rep("B", 12) , rep("C", 18)), col2=c( sample(2:5, 10 , replace=T) , sample(4:10, 12 , replace=T), sample(1:7, 18 , replace=T)))# plotting the data frameggplot(data_frame, aes(x = col1, y = col2, fill = col1)) + # adding violin plot geom_violin() |
Output:
Violinplot with Data Points in R
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