Grouping Numeric Data
Continuous numeric data can be transformed into categories using the cut() function. This is helpful when you want to analyze ranges rather than individual values.
Function Overview
The cut() function divides numbers into intervals and returns a factor:
cut(x, breaks, labels = NULL, right = TRUE, ordered_result = FALSE)
x: numeric vector to categorize;breaks: number of intervals or specific cut points;labels: names for categories;right: whether intervals are closed on the right;ordered_result: whether the categories should be ordered.
Example
12345678910heights <- c(170, 165, 195, 172, 189, 156, 178, 198, 157, 182, 171, 184, 163, 176, 169, 153) # Split heights into 3 groups heights_f <- cut(heights, breaks = c(0, 160, 190, 250), labels = c('short', 'medium', 'tall'), ordered_result = TRUE) heights_f
As a result:
- The data is divided into three intervals:
(0,160],(160,190], and(190,250]; - They are labeled as
'short','medium', and'tall'; - The categories follow a natural order.
Swipe to start coding
You have a vector of numerical grades. Here's how to categorize them as factor levels:
[0, 60)-'F';[60, 75)-'D';[75, 85)-'C';[85, 95)-'B';[95, 100)-'A'.
Your task is to:
- Create a variable called
grades_fthat categorizes the grades using thecut()function. Use the following parameters:breaks-c(0, 60, 75, 85, 95, 100);labels-c('F', 'D', 'C', 'B', 'A');ordered_result-TRUE(to order the factor values);right-FALSE(to include the left boundary of an interval, not the right).
- Output the contents of
grades_f.
Oplossing
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Continuous numeric data can be transformed into categories using the cut() function. This is helpful when you want to analyze ranges rather than individual values.
Function Overview
The cut() function divides numbers into intervals and returns a factor:
cut(x, breaks, labels = NULL, right = TRUE, ordered_result = FALSE)
x: numeric vector to categorize;breaks: number of intervals or specific cut points;labels: names for categories;right: whether intervals are closed on the right;ordered_result: whether the categories should be ordered.
Example
12345678910heights <- c(170, 165, 195, 172, 189, 156, 178, 198, 157, 182, 171, 184, 163, 176, 169, 153) # Split heights into 3 groups heights_f <- cut(heights, breaks = c(0, 160, 190, 250), labels = c('short', 'medium', 'tall'), ordered_result = TRUE) heights_f
As a result:
- The data is divided into three intervals:
(0,160],(160,190], and(190,250]; - They are labeled as
'short','medium', and'tall'; - The categories follow a natural order.
Swipe to start coding
You have a vector of numerical grades. Here's how to categorize them as factor levels:
[0, 60)-'F';[60, 75)-'D';[75, 85)-'C';[85, 95)-'B';[95, 100)-'A'.
Your task is to:
- Create a variable called
grades_fthat categorizes the grades using thecut()function. Use the following parameters:breaks-c(0, 60, 75, 85, 95, 100);labels-c('F', 'D', 'C', 'B', 'A');ordered_result-TRUE(to order the factor values);right-FALSE(to include the left boundary of an interval, not the right).
- Output the contents of
grades_f.
Oplossing
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