R Expert

This is a comprehensive R programming reference that covers everything from basic vectors and data frames through tidyverse operations, ggplot2 visualizations, and statistical modeling. You'll reach for it when working with data analysis pipelines, building regression models, or creating publication-ready plots. The examples are practical and production-focused, covering dplyr chains, time series forecasting with ARIMA, and machine learning with caret and randomForest. It includes R Markdown templates for reproducible reports and best practices around vectorization and code style. The statistical analysis section is solid, walking through t-tests, ANOVA, and logistic regression with assumption checking. If you're doing data science work in R, this gives you patterns you can copy and adapt rather than searching Stack Overflow.

skills.sh installs: 324
GitHub stars: 44
last updated: Aug 21, 2026

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Install

$ npx -y skills add personamanagmentlayer/pcl --skill r-expert --agent claude-code

Installs into .claude/skills of the current project.

Files

R Statistical Computing Expert

Expert guidance for R programming, statistical analysis, data visualization, and data science.

Core Concepts

R Fundamentals

Vectors and data frames
Factors and lists
Functions and apply family
Packages and libraries
R Markdown
Tidyverse ecosystem

Statistical Analysis

Descriptive statistics
Hypothesis testing
Regression analysis
ANOVA
Time series analysis
Machine learning

Data Visualization

ggplot2
Base R graphics
Interactive plots (plotly)
Statistical charts
Maps and spatial data

R Basics

# Vectors
numbers <- c(1, 2, 3, 4, 5)
names <- c("Alice", "Bob", "Charlie")

# Data frames
df <- data.frame(
  id = 1:5,
  name = c("Alice", "Bob", "Charlie", "David", "Eve"),
  age = c(25, 30, 35, 28, 32),
  salary = c(50000, 60000, 55000, 52000, 58000)
)

# Subsetting
df[df$age > 30, ]  # Rows where age > 30
df[, c("name", "age")]  # Select columns

# Functions
calculate_mean <- function(x) {
  sum(x) / length(x)
}

# Apply family
sapply(df$age, function(x) x * 2)
lapply(list(1:5, 6:10), sum)

SKILL.md on GitHub