Suppose you're working with a large dataset in R and need to categorize a numeric column into 'low', 'medium', and 'high' based on specific thresholds. How would you approach this?
- Use the cut() function to create categorical bins based on the thresholds
- Use nested if-else statements to evaluate each threshold condition
- Use the ifelse() function with multiple conditions for categorization
- Use the dplyr package's mutate() function with case_when() for conditional categorization
To categorize a numeric column into 'low', 'medium', and 'high' based on specific thresholds in R, you can use the cut() function. This function allows you to create categorical bins based on the thresholds. For example, you can specify the thresholds as breaks and assign labels 'low', 'medium', and 'high' to each category.
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