Apprendre 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


              12345678910
            
heights <- 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.

Tâche

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_f that categorizes the grades using the cut() 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.

Solution

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Section 1. Chapitre 25

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