TidyTuesday

A collection of visualizations for Tidy Tuesdays, built as a Quarto website with R and Python support.

🌐 Website

Visit the live website: here

🚀 Development Setup

Prerequisites

• R (≥4.4.0)
• Python (≥3.13)
• Quarto
• uv (Python package manager)

Quick Start

1. Clone the repository:

   git clone https://github.com/gnoblet/TidyTuesday.git
   cd TidyTuesday

2. Run the setup script:

   ./setup-dev.sh

3. Preview the website:

   quarto preview

📝 Creating New Visualizations

Use the included script to generate a new visualization from the template in R:

# Create a new R post from the template
# Usage:
#   Rscript posts/new-viz-from-template.R [-c "categories"] [-u "tools used"] [-k "key libraries"] [-f image_file] <date> <title>
#
# Notes:
#  - Creates: posts/<YEAR>/week_<N>/week_<N>.qmd
#  - Default image filename: weekNN.png (zero-padded) placed inside that week folder, e.g. posts/2025/week_01/week01.png
#  - The script replaces placeholders in template.qmd; ensure template.qmd is present.
#  - The script will update _quarto.yml to add the new post entry when possible.
#  - Week number = ISO week of the date minus one (keeps existing behavior).

# Examples
# Minimal (uses defaults and weekXX.png):
Rscript new-viz-from-template.R 2025-01-07 "Coffee Analysis"

# With metadata flags and explicit image name:
Rscript new-viz-from-template.R \
  -c "ggplot2, tidyverse" \
  -u "R, ggplot2, tidyverse" \
  -k "ggplot2, dplyr, tidyr" \
  -f week01.png \
  2025-01-07 "Coffee Analysis"

# If you only want to override the image name:
Rscript new-viz-from-template.R -f custom-plot.png 2025-01-07 "Coffee Analysis"

# Quick help:
Rscript new-viz-from-template.R -h

Arguments:

• date: Date in YYYY-MM-DD format (e.g., 2024-12-15)
• title: Title for the analysis (use quotes if it contains spaces)
• -c "categories": Comma-separated categories (default: "TidyTuesday")
• -u "tools used": Comma-separated tools used (default: "R
• -k "key libraries": Comma-separated key libraries (default: "ggplot2, dplyr")
• -f image_file: Filename for the main visualization image (default: weekNN.png

This will create:

• A .qmd file in the posts/ directory with a complete template
• All placeholders automatically replaced with your specified values
• Ready-to-edit analysis structure

Automatic Gallery Integration

• New analyses automatically appear in the gallery when you render the site
• No manual updates needed - the gallery scans for .qmd files dynamically
• Consistent formatting across all projects

Manual Setup

R Environment (renv)

# Restore R packages
R -e "renv::restore()"

Python Environment (uv)

# Create virtual environment
uv venv .venv
source .venv/bin/activate

# if using fish instead of bash
source .venv/bin/activate.fish

# Install dependencies
uv sync

Build Website

# Render the website
quarto render

# Preview locally
quarto preview

📁 Project Structure

├── .github/workflows/   # GitHub Actions for deployment
├── posts/               # Project posts (Quarto)
├── _site/               # Generated website (ignored)
├── renv/                # R environment
├── .venv/               # Python virtual environment (ignored)
├── requirements.txt     # Python dependencies
├── renv.lock            # R package lockfile
└── _quarto.yml          # Quarto configuration

🔄 Deployment

The website is automatically deployed to GitHub Pages when changes are pushed to the main branch. The GitHub Actions workflow:

1. Sets up R with renv for package management
2. Sets up Python with uv for package management
3. Installs system dependencies
4. Renders the Quarto website
5. Deploys to GitHub Pages

🛠️ Package Management

• R packages: Managed by renv
• Python packages: Managed by uv
• Repository: Fast Linux binaries from p3m.dev

📄 License

This project is open source and available under the MIT License.