R quantile() Function - Calculating Quantiles
R Language ExampleThe R quantile() function is used to calculate the quantiles of data.
Quantiles are points that divide data proportionally after sorting. For example, the median is the 50% quantile.
The syntax format of the quantile() function is as follows:
quantile(x, probs = seq(0, 1, 0.25), na.rm = FALSE)
Parameter description:
xInput numeric vector.
probsQuantile probability values, ranging from 0 to 1. By default, returns quartiles (0, 0.25, 0.5, 0.75, 1).
na.rmBoolean value, sets whether to remove missing values NA.
Example
# Create exam scores
scores <- c(55, 62, 68, 70, 72, 75, 78, 80, 82, 85,
88, 90, 92, 95, 98)
# Default quartiles
print("Quartiles:")
print(quantile(scores))
# Custom quantile points
print("Custom quantile points (10%, 50%, 90%):")
print(quantile(scores, probs = c(0.1, 0.5, 0.9)))
scores <- c(55, 62, 68, 70, 72, 75, 78, 80, 82, 85,
88, 90, 92, 95, 98)
# Default quartiles
print("Quartiles:")
print(quantile(scores))
# Custom quantile points
print("Custom quantile points (10%, 50%, 90%):")
print(quantile(scores, probs = c(0.1, 0.5, 0.9)))
The output of executing the above code is:
[1] "四分位数:" 0% 25% 50% 75% 100% 55.00 71.00 80.00 88.75 98.00 [1] "自定义分位点 (10%, 50%, 90%):" 10% 50% 90% 63.2 80.0 94.4
quantile() is often used to identify data distribution characteristics and detect outliers:
Example
# Use the IQR method to detect outliers
scores <- c(55, 62, 68, 70, 72, 75, 78, 80, 82, 85, 120)
# Calculate Q1, Q3, and IQR
Q1 <- quantile(scores, 0.25)
Q3 <- quantile(scores, 0.75)
IQR <- Q3 - Q1
# Outlier boundaries
lower_bound <- Q1 - 1.5 * IQR
upper_bound <- Q3 + 1.5 * IQR
print(paste("Normal range:", round(lower_bound, 1), "to", round(upper_bound, 1)))
# Find outliers
outliers <- scores[scores < lower_bound | scores > upper_bound]
print(paste("Outliers:", outliers))
scores <- c(55, 62, 68, 70, 72, 75, 78, 80, 82, 85, 120)
# Calculate Q1, Q3, and IQR
Q1 <- quantile(scores, 0.25)
Q3 <- quantile(scores, 0.75)
IQR <- Q3 - Q1
# Outlier boundaries
lower_bound <- Q1 - 1.5 * IQR
upper_bound <- Q3 + 1.5 * IQR
print(paste("Normal range:", round(lower_bound, 1), "to", round(upper_bound, 1)))
# Find outliers
outliers <- scores[scores < lower_bound | scores > upper_bound]
print(paste("Outliers:", outliers))
The output of executing the above code is:
[1] "正常范围: 44.3 到 119.3" [1] "异常值: 120"Other Extensions