https://github.com/iremaydas/base-r-skill
Provides base R programming guidance covering data structures, data wrangling, statistical modeling, visualization, and I/O
https://github.com/iremaydas/base-r-skill
claude-skills data-analysis r skills
Last synced: 4 days ago
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Provides base R programming guidance covering data structures, data wrangling, statistical modeling, visualization, and I/O
- Host: GitHub
- URL: https://github.com/iremaydas/base-r-skill
- Owner: iremaydas
- License: mit
- Created: 2026-03-27T11:49:02.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2026-03-27T11:58:00.000Z (3 months ago)
- Last Synced: 2026-03-27T22:55:30.158Z (3 months ago)
- Topics: claude-skills, data-analysis, r, skills
- Language: R
- Homepage:
- Size: 35.2 KB
- Stars: 3
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# base-r-skill
A [Claude Code](https://claude.ai/code) skill for base R programming.
---
## The Story
I'm a political science PhD candidate who uses R regularly but would never call myself *an R person*. I needed a Claude Code skill for base R — something without tidyverse, without ggplot2, just plain R — and I couldn't find one anywhere.
So I made one myself. At 11pm. Asking Claude to help me build a skill for Claude.
If you're also someone who Googles `how to drop NA rows in R` every single time, this one's for you. 🫶
---
## What's Inside
```
base-r/
├── SKILL.md # Main skill file
├── references/ # Gotchas & non-obvious behaviors
│ ├── data-wrangling.md # Subsetting traps, apply family, merge, factor quirks
│ ├── modeling.md # Formula syntax, lm/glm/aov/nls, optim
│ ├── statistics.md # Hypothesis tests, distributions, clustering
│ ├── visualization.md # par, layout, devices, colors
│ ├── io-and-text.md # read.table, grep, regex, format
│ ├── dates-and-system.md # Date/POSIXct traps, options(), file ops
│ └── misc-utilities.md # tryCatch, do.call, time series, utilities
├── scripts/
│ ├── check_data.R # Quick data quality report for any data frame
│ └── scaffold_analysis.R # Generates a starter analysis script
└── assets/
└── analysis_template.R # Copy-paste analysis template
```
The reference files were condensed from the official R 4.5.3 manual — **19,518 lines → 945 lines** (95% reduction). Only the non-obvious stuff survived: gotchas, surprising defaults, tricky interactions. The things Claude already knows well got cut.
---
## How to Use
Add this skill to your Claude Code setup by pointing to this repo. Then Claude will automatically load the relevant reference files when you're working on R tasks.
Works best for:
- Base R data manipulation (no tidyverse)
- Statistical modeling with `lm`, `glm`, `aov`
- Base graphics with `plot`, `par`, `barplot`
- Understanding why your R code is doing that weird thing
Not for: tidyverse, ggplot2, Shiny, or R package development.
---
## The `check_data.R` Script
Probably the most useful standalone thing here. Source it and run `check_data(df)` on any data frame to get a formatted report of dimensions, NA counts, numeric summaries, and categorical breakdowns.
```r
source("scripts/check_data.R")
check_data(your_df)
```
---
## Built With Help From
- Claude (obviously)
- The official R manuals (all 19,518 lines of them)
- Mild frustration and several cups of coffee
---
## Contributing
If you spot a missing gotcha, a wrong default, or something that should be in the references — PRs are very welcome. I'm learning too.
---
*Made by [@iremaydas](https://github.com/iremaydas) — PhD candidate, occasional R user, full-time Googler of things I should probably know by now.*