How to Make a Great R Reproducible Example?

How to Make a Great R Reproducible Example?

Have you ever posted a question about R on forums like Stack Overflow and received the dreaded response: "Can you provide a reproducible example?"? Crafting a good reproducible example is the key to getting the help you need. In this guide, you'll learn how to create a concise, clear, and complete example that others can easily run and debug.

What Is a Reproducible Example?

A reproducible example (or reprex) is a minimal, self-contained piece of code that replicates an issue or demonstrates a concept. It allows others to quickly understand your problem without additional context or guesswork.

Pro Tip: Use the reprex package to make this process easier!

Steps to Create a Great Reproducible Example

1. Isolate the Problem

Start by identifying the smallest piece of code that reproduces your issue. Remove all unrelated elements like unused variables, extra functions, or unnecessary libraries.

# Example: Original messy code
library(ggplot2)
library(dplyr)
data <- read.csv("large_dataset.csv")
subset <- filter(data, age > 30)
ggplot(subset, aes(x = age, y = income)) +
  geom_point()

  

Becomes:

# Cleaned minimal example
library(ggplot2)
data <- data.frame(age = c(25, 35, 45), income = c(30000, 50000, 70000))
ggplot(data, aes(x = age, y = income)) +
  geom_point()

  

2. Include All Required Libraries

Ensure your example includes every library needed to run the code. Missing dependencies can make the example unusable for others.

3. Use Built-In or Simulated Data

Replace external datasets with built-in R datasets (like mtcars or iris) or simulated data. For example:

# Simulated data example
data <- data.frame(
  x = 1:10,
  y = rnorm(10)
)

  

4. Provide Expected Output

Show what the expected output looks like or describe what you expect versus what happens. This helps others pinpoint the issue faster.

# Expected output
# A scatter plot where points align along y = x.

  

5. Test Your Example

Run your code in a clean R session to ensure it works. Use sessionInfo() to provide details about your R environment if needed.

sessionInfo()
  

Using the reprex Package

The reprex package simplifies creating and sharing reproducible examples. Here's how to use it:

1. Install the package: install.packages("reprex")
2. Load it: library(reprex)
3. Run reprex() on your code:

# Example
reprex({
  x <- 1:5
  y <- x^2
  plot(x, y)
})

  

The output is ready to paste into forums or emails, formatted for easy sharing.

Conclusion

Creating a great R reproducible example is a skill that will save you time and increase the chances of getting effective help. Follow these steps, and you'll have clear, concise, and helpful examples that others can use to assist you.

Happy coding!