How to Calculate Quartiles in R?
In this article, we will discuss how to calculate quartiles in the R programming language.
Quartiles are just special percentiles that occur after a certain percent of data has been covered.
- First quartile: Refers to 25th percentile of the data. This depicts that 25% percent of data is under the produced value.
- Second quartile: Refers to 50th percentile of the data. This depicts that 50% percent of data is under the produced value. This is also the median of the data.
- Third quartile: Refers to the 75th percentile of the data. This predicts that 75% percent of the data is under the produced value.
To obtain the required quartiles, the quantile() function is used.
Syntax: quantile( data, probs)
Parameter:
- data: data whose percentiles are to be calculated
- probs: percentile value
Example 1: Calculate quartile in vector
R
x = c (2,13,5,36,12,50) res<- quantile (x, probs = c (0,0.25,0.5,0.75,1)) res |
Output:
0% 25% 50% 75% 100% 2.00 6.75 12.50 30.25 50.00
Example 2: Calculate quartile in dataframe
R
df<- data.frame (x = c (2,13,5,36,12,50), y = c ( 'a' , 'b' , 'c' , 'c' , 'c' , 'b' )) res<- quantile (df$x, probs = c (0,0.25,0.5,0.75,1)) res |
Output:
0% 25% 50% 75% 100% 2.00 6.75 12.50 30.25 50.00