Data Analysis Template

Rproj template for data analysis

Data analysis template: A Reproducible R Framework for PsychoPy Behavioral Experiments

I’m excited to share a new open-source project designed to streamline the process of analyzing behavioral data collected with PsychoPy:

👉 Data_analysis_template on GitHub

This template is ideal for researchers who collect .csv files from PsychoPy experiments and want a consistent, reusable R-based analysis workflow.

What It Does

The template provides:

A structured R project layout (R/, data/, original_data/, etc.)
Ready-to-use functions for common preprocessing steps
Support for saving results in .RData and .xlsx
A clean GitHub repository with MIT license and template button

Why Use It

This template was created to address common issues in behavioral science research:

Poor file organization
Redundant code copy-pasting between experiments
Inconsistent use of statistical functions
Lack of reproducibility

By providing a clear, modular R structure and helper functions, this project promotes transparency and makes it easy to replicate your own or others’ work.

What is an R Project (`.Rproj`)?

An R project file (.Rproj) defines a self-contained environment in RStudio. Think of it as a sandbox:

All your scripts, data, and outputs stay in one place
You don’t need to manage complex file paths — here::here() or relative paths work out of the box
It’s easy to share, version, and reproduce the analysis on another computer

In short: open the .Rproj file, and you’re ready to go.

Getting Started

You can start using the template in three easy ways:

1. Use it directly from GitHub

Click the green “Use this template” button:
👉 https://github.com/Merluin/Data_analysis_template

This creates a new copy under your own GitHub account, preserving the folder structure and code.
✨ Don’t forget to leave a ⭐ on the repository if you find it helpful!

2. Clone manually

git clone https://github.com/Merluin/Data_analysis_template.git

Then open Data_analysis.Rproj in RStudio and start analyzing.

3. Just download the ZIP

Click the “Code” button and select “Download ZIP”. Unzip it anywhere, open the .Rproj file, and you’re ready to go — no Git required.

📁 Project Structure

Data_analysis_template/
├── DESCRIPTION             # R package metadata
├── R/                      # All core analysis functions
├── data/                   # Cleaned datasets saved as .RData
├── original_data/          # Raw .csv files from PsychoPy
├── scripts/                # Custom analysis scripts (per experiment)
├── LICENSE                 # MIT License
├── README.md               # Project description
└── Data_analysis.Rproj     # RStudio project file