A five number summary is a way to summarize a dataset using the following five values:
- The minimum
- The first quartile
- The median
- The third quartile
- The maximum
The five number summary is useful because it provides a concise summary of the distribution of the data in the following ways:
- It tells us where the middle value is located, using the median.
- It tells us how spread out the data is, using the first and third quartiles.
- It tells us the range of the data, using the minimum and the maximum.
The easiest way to calculate a five number summary of a dataset in R is to use the fivenum() function from base R:
fivenum(data)
The following example shows how to use this syntax in practice.
Example 1: Five Number Summary of Vector
The following code shows how to calculate the five number summary of a numeric vector in R:
#define numeric vector
data #calculate five number summary of data
fivenum(data)
[1] 4 7 12 15 22
From the output we can see:
- The minimum: 4
- The first quartile: 7
- The median: 12
- The third quartile: 15
- The maximum: 22
We can quickly visualize the five number summary by creating a boxplot:
boxplot(data) [1] 4 7 12 15 22
Here’s how to interpret the boxplot:
- The line at the bottom of the plot represents the minimum value (4).
- The line at the bottom of the box represents the first quartile (7).
- The line in the middle of the box represents the median (12).
- The line at the top of the box represents the third quartile (15).
- The line at the top of the plot represents the maximum value (22).
Example 2: Five Number Summary of Column in Data Frame
The following code shows how to calculate the five number summary of a specific column in a data frame:
#create data frame df frame(team=c('A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'), points=c(99, 90, 86, 88, 95, 87, 85, 89), assists=c(33, 28, 31, 39, 34, 30, 29, 25), rebounds=c(30, 28, 24, 24, 28, 30, 31, 35)) #calculate five number summary of points column fivenum(df$points) [1] 85.0 86.5 88.5 92.5 99.0
Example 3: Five Number Summary of Multiple Columns
The following code shows how to use the sapply() function to calculate the five number summary of several columns in a data frame at once:
#create data frame df frame(team=c('A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'), points=c(99, 90, 86, 88, 95, 87, 85, 89), assists=c(33, 28, 31, 39, 34, 30, 29, 25), rebounds=c(30, 28, 24, 24, 28, 30, 31, 35)) #calculate five number summary of points, assists, and rebounds column sapply(df[c('points', 'assists', 'rebounds')], fivenum) points assists rebounds [1,] 85.0 25.0 24.0 [2,] 86.5 28.5 26.0 [3,] 88.5 30.5 29.0 [4,] 92.5 33.5 30.5 [5,] 99.0 39.0 35.0
Related:Â A Guide to apply(), lapply(), sapply(), and tapply() in R
Additional Resources
How to Create Summary Tables in R
How to Find the Range in R
How to Remove Outliers in R