Optional arguments
Let's look at some of the round() function's help documentation. It simply rounds a numeric vector off to a specified number of decimal places.
round(x, digits = 0)
The first argument, x is required. Without it, the function will not work!
The argument digits is known as an optional argument. Optional arguments are ones that don't have to be set by the user, either because they are given a default value, or because the function can infer them from the other data you have given it. Even though they don't have to be set, they often provide extra flexibility. Here, digits specifies the number of decimal places to round to.
Explore the round() function in the exercise!
This is a part of the course
“Intermediate R for Finance”
Exercise instructions
- Use
round()on5.4. - Use
round()on5.4, specifydigits = 1. - A vector
numbershas been created for you. - Use
round()onnumbersand specifydigits = 3.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Round 5.4
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# Round 5.4 with 1 decimal place
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numbers <- c(.002623, pi, 812.33345)
# Round numbers to 3 decimal places
___This exercise is part of the course
Intermediate R for Finance
Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.
If data structures like data frames and vectors are how you hold your data, functions are how you tell R what to do with your data. In this chapter, you will learn about using built-in functions, creating your own unique functions, and you will finish off with a brief introduction to packages.
Exercise 1: What are functions?Exercise 2: Function help and documentationExercise 3: Optional argumentsExercise 4: Functions in functionsExercise 5: Writing functionsExercise 6: Your first functionExercise 7: Multiple arguments (1)Exercise 8: Multiple arguments (2)Exercise 9: Function scope (1)Exercise 10: Function scope (2)Exercise 11: PackagesExercise 12: tidyquant packageWhat is DataCamp?
Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.