R
A comprehensive skill catalog for AI agents
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R statistical programming for data analysis, visualization, and modeling. Use for .r files.
SKILL.md
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R
A language and environment for statistical computing and graphics.
When to Use
- Statistical Analysis
- Data Visualization (ggplot2)
- Bioinformatics
- Academic research
Quick Start
print("Hello, World!")
# Vector
x <- c(1, 2, 3, 4, 5)
# Mean
mean(x)
# Data Frame
df <- data.frame(
Name = c("Alice", "Bob"),
Age = c(25, 30)
)
Core Concepts
Vectorization
R operations are designed to work on entire vectors at once, avoiding explicit loops.
x + 1 # Adds 1 to every element in x
Pipe Operator %>%
Used to clean code by passing output of one function as input to the next (Tidyverse).
data %>%
filter(users > 100) %>%
group_by(region) %>%
summarize(total = sum(users))
Best Practices
Do:
- Use the Tidyverse (dplyr, ggplot2) for modern R
- Document functions with Roxygen2
- Use RStudio IDE
Don't:
- Use explicit
forloops if vectorization is possible (performance) - Mix naming conventions (snake_case is preferred in tidyverse)