How to create a violin plot using plotly in R?
This recipe helps you create a violin plot using plotly in R
Recipe Objective
Violin plots are similar to boxplots which showcases the probability density along with interquartile, median and range at different values. They are more informative than boxplots which are used to showcase the full distribution of the data. They are also known to combine the features of histogram and boxplots. They are mainly used to compare the distribution of different variables/columns in the dataset.
In this recipe we are going to use Plotly package to plot the required violin plot. Plotly package provides an interface to the plotly javascript library allowing us to create interactive web-based graphics entrirely in R. Plots created by plotly works in multiple format such as:
- R Markdown Documents
- Shiny apps - deploying on the web
- Windows viewer
Plotly has been actively developed and supported by it's community.
This recipe demonstrates how to plot a violin plot in R using plotly package.
STEP 1: Loading required library and dataset
Dataset description: It is the basic data about the customers going to the supermarket mall. The variable that we are interested in: Annual.Income (which is in 1000s), Spending Score and age
# Data manipulation package
library(dplyr)
library(tidyverse)
# reading a dataset
customer_seg = read.csv('R_132_Mall_Customers.csv')
# selecting the required variables using the select() function
customer_seg_var = select(customer_seg, Age, Annual.Income..k..,Spending.Score..1.100.)
# summary of the selected variables
glimpse(customer_seg_var)
Observations: 200 Variables: 3 $ Age19, 21, 20, 23, 31, 22, 35, 23, 64, 30, 67, 35… $ Annual.Income..k.. 15, 15, 16, 16, 17, 17, 18, 18, 19, 19, 19, 19… $ Spending.Score..1.100. 39, 81, 6, 77, 40, 76, 6, 94, 3, 72, 14, 99, 1…
STEP 2: Plotting a Violin plot using Plotly
We use the plot_ly() function to plot a box plot between of Annual Income based on Gender.
Syntax: plot_ly( data = , x = , y = , type = "violin")
Where:
- x = variable to be plotted in x axis
- y = variable to be plotted in y axis
- data = dataframe to be used
- type = type of the chart
Note:
- The %>% sign in the syntax earlier makes the code more readable and enables R to read further code without breaking it.
- We also use layout() function to give a title to the graph
fig <- plot_ly(x = ~Gender, y = ~Annual.Income..k..,
data = customer_seg,
type = "violin",
# to also plot box plot whiskers on top of the violin plot
box = list(visible = T)) %>% layout(title = 'Violin Plot using Plotly')
embed_notebook(fig)
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Ed Godalle
I am the Director of Data Analytics with over 10+ years of IT experience. I have a background in SQL, Python, and Big Data working with Accenture, IBM, and Infosys. I am looking to enhance my skills... Read More