Histogram in R using ggplot2
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 :
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