Histogram in R using ggplot2 - GeeksforGeeks

25 Feb, 2021

ggplot2 is an R Package that is dedicated to Data visualization. ggplot2 Package  Improve the quality and the beauty (aesthetics ) of the graph. By Using ggplot2 we can make almost every kind of graph In RStudio
A histogram is an approximate representation of the distribution of numerical data. In a histogram, each bar groups numbers into ranges. Taller bars show that more data falls in that range. A histogram displays the shape and spread of continuous sample data.
Histograms roughly give us an idea about the probability distribution of a given variable by depicting the frequencies of observations occurring in certain ranges of values. Basically, Histograms are used to show distributions of a given variable while bar charts are used to compare variables. Histograms plot quantitative data with ranges of the data grouped into the intervals while bar charts plot categorical data.
geom_histogram() function is an in-built function of ggplot2 module.
Approach
Import module
Create dataframe
Create histogram using function
Display plot
Example 1:
R
 

 
 










set.seed(123) 
  
# In the above line,123 is set as the  
# random number value 
# The main point of using the seed is to 
# be able to reproduce a particular sequence  
# of 'random' numbers. and sed(n) reproduces 
# random numbers results by seed 
df <- data.frame( 
   gender=factor(rep(c( 
     "Average Female income ", "Average Male incmome"), each=20000)), 
   Average_income=round(c(rnorm(20000, mean=15500, sd=500),  
                          rnorm(20000, mean=17500, sd=600)))    
)   
head(df) 
  
# if already installed ggplot2 then use library(ggplot2) 
library(ggplot2) 
  
# Basic histogram 
ggplot(df, aes(x=Average_income)) + geom_histogram() 
  
# Change the width of bins 
ggplot(df, aes(x=Average_income)) +     
  
   geom_histogram(binwidth=1) 
  
# Change colors 
p<-ggplot(df, aes(x=Average_income)) +    
  
   geom_histogram(color="white", fill="red") 
p






Output : 
Example 2:
R
 

 
 










plot_hist <- ggplot(airquality, aes(x = Ozone)) + 
  
   # binwidth help to change the thickness (Width) of the bar  
   geom_histogram(aes(fill = ..count..), binwidth = 10)+ 
  
   # name = "Mean ozone(03) in ppm parts per million " 
   # name is used to give name to axis   
   scale_x_continuous(name = "Mean ozone(03) in ppm parts per million ", 
                      breaks = seq(0, 200, 25), 
                      limits=c(0, 200)) + 
   scale_y_continuous(name = "Count") + 
  
   # ggtitle is used to give name to a chart 
   ggtitle("Frequency of mean ozone(03)") + 
   scale_fill_gradient("Count", low = "green", high = "red") 
  
plot_hist






Output : 

Picked


R-Charts


R-Graphs


R-plots


R Language

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