- Data Structure
- Networking
- RDBMS
- Operating System
- Java
- MS Excel
- iOS
- HTML
- CSS
- Android
- Python
- C Programming
- C++
- C#
- MongoDB
- MySQL
- Javascript
- PHP
- Physics
- Chemistry
- Biology
- Mathematics
- English
- Economics
- Psychology
- Social Studies
- Fashion Studies
- Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
How to create density plot for categories in R?
To create density plot for categories, we can follow the below steps −
- Frist of all, create a data frame.
- Load ggplot2 package and creating the density plot for the whole data.
- Create the density plot for the categories in the data frame by using col function.
Create the data frame
Let's create a data frame as shown below −
x<-sample(LETTERS[1:3],20,replace=TRUE) y<-sample(1:100,20) df<-data.frame(x,y) df
On executing, the above script generates the below output(this output will vary on your system due to randomization) −
x y 1 A 47 2 B 46 3 B 29 4 C 53 5 C 60 6 C 17 7 B 79 8 B 12 9 B 30 10 C 91 11 A 92 12 A 2 13 B 25 14 B 98 15 B 88 16 C 34 17 C 50 18 A 20 19 C 90 20 B 87
Loading ggplot2 package and creating a density plot for whole data
library(ggplot2) x<-sample(LETTERS[1:3],20,replace=TRUE) y<-sample(1:100,20) df<-data.frame(x,y) ggplot(df,aes(y))+geom_density()
Output
Create density plot based on categories
Use col function inside aes of geom_density function to create the density plot based on categories −
library(ggplot2) x<-sample(LETTERS[1:3],20,replace=TRUE) y<-sample(1:100,20) df<-data.frame(x,y) ggplot(df,aes(y))+geom_density(aes(col=x),alpha=0.2)
Output
Advertisements