editor_options	markdown wrap 72

R Project Template

A standardized template for organizing R data analysis projects with built-in Git LFS support for large files.

Repository Structure

Project/
├── 01_data/
│   ├── 01_raw_files/              # Original, unmodified datasets
│   ├── 02_processed_files/        # Cleaned or transformed datasets
│   ├── 03_large_files_LFS/        # Large datasets tracked via Git LFS
│   └── 04_gitignore_files/        # Local-only files, never committed
├── 02_scripts/
│   └── 01_functions/              # Reusable R functions
├── 03_outputs/
│   └── 01_figures/                # Generated plots and visualizations
├── 04_notes/                      # Project documentation and guides
├── .gitignore                     # Files excluded from version control
├── .gitattributes                 # Git LFS configuration
└── README.md                      # This file

Quick Start

1. Clone or Copy This Template

# If using as a template for a new project
git clone <this-repo-url> <your-project-name>
cd <your-project-name>

2. Set Up Git LFS (One-Time Setup)

If you haven't installed Git LFS before:

# Install Git LFS (Windows - included with Git for Windows)
git lfs version  # Verify installation

# Configure Git LFS on your machine (once per user)
git lfs install

For detailed installation and troubleshooting, see: 04_notes/git_lfs_setup.md

3. Start Working

• Add data files to 01_data/ (large files go in 03_large_files_LFS/)
• Create analysis scripts in 02_scripts/
• Store custom functions in 02_scripts/01_functions/
• Generated outputs automatically go to 03_outputs/

Directory Descriptions

01_data/

Store all input data files here: - Raw data: Original, unmodified datasets - Processed data: Cleaned or transformed datasets - 03_large_files_LFS/: Large datasets automatically tracked via Git LFS

02_scripts/

Analysis and processing scripts: - Main scripts: Numbered workflows (scriptXX-YY format) - 01_functions/: Reusable functions sourced by multiple scripts - Organize scripts by dependency order using numbered prefixes

03_outputs/

Generated results and visualizations: - 01_figures/: Plots, maps, and visualizations - Tables: Summary statistics and model outputs - Reports: Rendered R Markdown documents

Note: Output files are gitignored by default to ensure reproducibility

04_notes/

Project documentation and guides: - Analysis notes and decisions - Methodology documentation - Setup guides

Git Configuration

What's Tracked

• All R scripts (.R, .Rmd)
• Data files in 01_data/ (via Git LFS for large files)
• Project configuration files (.Rproj, .gitignore, .gitattributes)
• Documentation (.md files)

What's Ignored

See .gitignore for complete list: - R session files (.RData, .Rhistory, .Rproj.user/) - Generated outputs (.png, .pdf, .tiff, etc.) - Temporary objects

Git LFS

Files in 01_data/03_large_files_LFS/ are automatically tracked via Git LFS: - Prevents repository bloat from large datasets - Maintains version control for large files - Works transparently once configured

See 04_notes/git_lfs_setup.md for complete setup instructions

Coding Conventions

This template follows standardized R coding practices for file naming, folder organization, and R object naming.

Naming Convention Overview

Files and Folders:

• Scripts: scriptXX-YY_descriptive_name.R (e.g., script02-01_analysis_rf.R)
• Functions: fctXX-YY_descriptive_name.R (e.g., fct01-01_helper_functions.R)
• Folders: XX_descriptive_name/ (e.g., 01_data/, 02_scripts/)
• All lowercase with underscores

R Objects:

• Raw data: data_* (e.g., data_habitat)
• Processed data: df_* (e.g., df_habitat_clean)
• Parameters: param_* (e.g., param_seed)
• Temporary: temp_* (e.g., temp_filtered)

See 04_notes/naming_conventions.md for complete details.

Workflow Recommendations

Script Organization

• script00-XX: Setup (packages, functions, configuration)
• script01-XX: Data import and formatting
• script02-XX: Analysis workflows
• script03-XX: Visualization and reporting
• script10-XX: Special analyses or extensions

Master Control Script

Use script00-00_user_interface.R to orchestrate your workflow:

• Source package loading script
• Load data objects
• Execute analysis scripts in dependency order
• Provide workflow documentation

Version Control

1. Commit often with descriptive messages
2. Document changes in script modification notes
3. Use branches for experimental analyses

Additional Documentation

• Naming Conventions: Complete guide to file, folder, and object naming
• Git LFS Setup: Installation, configuration, and troubleshooting

External Resources

• R for Data Science
• Git LFS Documentation
• Happy Git with R