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How to Add Vertical Lines By a Variable in Multiple Density Plots with ggplot2 in R

  • Last Updated : 24 Oct, 2021

In this article, we will discuss how to add vertical lines by a variable in multiple density plots with ggplot2 package in the R  Programming language. 

To do so first we will create multiple density plots colored by group and then add the line as a separate element.

Basic Multiple Density Plot:

To make multiple density plots with coloring by variable in R with ggplot2, we firstly make a data frame with values and category. Then we draw the ggplot2 density plot using the geom_desnity() function. To color them according to the variable we add the fill property as a category in the ggplot() function.

Syntax: 

ggplot(dataFrame, aes( x, color, fill)) + geom_density()



Example:

We get multiple density plots in the ggplot of two colors corresponding to two-level/values for the second categorical variable. If our categorical variable has n levels, then ggplot2 would make multiple density plots with n densities/color.

R




# load library
library(tidyverse)
  
set.seed(1234)
  
# create the dataframe
df <- data.frame(
    category=factor(rep(c("category1", "category2","category3"),
                        each=1000)),
    value=round(c(rnorm(1000, mean=65, sd=5),
                  rnorm(1000, mean=85, sd=5),
                 rnorm(1000, mean=105, sd=5))))
  
  
  
# Basic density plot with custom color
# color property to determine the color of plot
# fill property to determine the color beneath plot
ggplot(df, aes(x=value, color=category, fill=category)) +
geom_density(alpha=0.3)

Output:

Adding Line by a variable

To add a line by a variable to plot create a new data frame median to a data frame that stores the median of values grouped by categories. Then use the geom_vline function to draw a line across that point colored by category of data.

Syntax:

plot + geom_vline( dataframe, aes( xintercept, color ), size)



Example:

Here, we have calculated the median of values grouped by category and stored it in a data frame named median. Then used geom_vline() function to draw a line across the plot at that point colored according to the category of data.

To create a Median data frame we use,

median <- df %>%
             group_by(category) %>%
             summarize(median=median(value))

Median data frame made from group_by and summarize function looks like:

# A tibble: 3 x 2
 category  median
 <fct>      <dbl>
1 category1     65
2 category2     85
3 category3    105

R




# load library
library(tidyverse)
  
set.seed(1234)
df <- data.frame(
    category=factor(rep(c("category1", "category2","category3"), 
                        each=1000)),
    value=round(c(rnorm(1000, mean=65, sd=5),
                  rnorm(1000, mean=85, sd=5),
                 rnorm(1000, mean=105, sd=5))))
  
  
# create median data using above dataframe
# group_by function groups the data of same category
# summarize function with median
# argument calculates the median of value column
median <- df %>%
  group_by(category) %>%
  summarize(median=median(value))
  
  
# Basic density plot with custom color
# color property to determine the color of plot
# fill property to determine the color beneath plot
# geom_vline function draws the line across median 
# of each group
ggplot(df, aes(x=value, color=category, fill=category)) +
geom_density(alpha=0.3)+
  geom_vline(data = median, aes(xintercept = median, 
                                       color = category), size=0.5)

Output:




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