How to Find and Visualize Quartiles in R


Quartiles are values that split up a dataset into four equal parts.

  • The first quartile represents the 25th percentile of a dataset.
  • The second quartile represents the 50th percentile of a dataset. This value is equivalent to the median value of the dataset.
  • The third quartile represents the 75th percentile of a dataset.

We can easily calculate the quartiles of a given dataset in R by using the quantile() function. This tutorial provides examples of how to use this function in practice.

Calculating Quartiles in R

The following code shows how to calculate the quartiles of a given dataset in R:

#define dataset
data = c(4, 7, 12, 13, 14, 15, 15, 16, 19, 23, 24, 25, 27, 28, 33)

#calculate quartiles of dataset
quantile(data)

  0%  25%  50%  75% 100% 
 4.0 13.5 16.0 24.5 33.0 

Here’s how to interpret the output:

  • The first value displays the minimum value in the dataset: 4.0
  • The second value displays the first quartile of the dataset: 13.5
  • The third value displays the second quartile of the dataset: 16.0
  • The fourth value displays the third quartile of the dataset: 24.5
  • The fifth value displays the maximum value in the dataset: 33.0

Related: How to Easily Calculate Percentiles in R

Visualizing Quartiles in R

We can use the boxplot() function to create a boxplot to visualize the quartiles of this dataset in R:

#create boxplot 
boxplot(data)

Visualizing quartiles in R

Here’s how to interpret the boxplot:

  • The bottom “whisker” displays the minimum value of 4.
  • The bottom line of the box displays the first quartile value of 13.5.
  • The black bar in the middle of the box displays the second quartile value of 16.0.
  • The top line of the box displays the third quartile value of 24.5.
  • The top “whisker” displays the maximum value of 33.0.

This single plot helps us quickly visualize the distribution of values in the dataset.

Related: How to Plot Multiple Boxplots in One Chart in R

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