retire-coal 0.1.0

A data-driven approach to strategizing US coal plant retirement using network analysis and contextual vulnerabilities.

Retire

⚠️ Work in Progress: This is a v0 release. Features and APIs may change.

A Python package for US coal plant retirement analysis based on research published in Nature Energy. Provides data and analysis tools for understanding coal plant retirement strategies using contextual vulnerabilities.

Key Features

• Comprehensive Dataset: Detailed coal plant data with operational and contextual factors
• Network Analysis: Analyze plant relationships using similarity metrics
• Visualization Suite: Rich plotting capabilities for retirement patterns
• Research Reproducibility: Access to manuscript results and analysis

Quick Start

Installation

git clone https://github.com/Krv-Analytics/retire.git
cd retire
pip install uv
uv sync

Note: This package will soon be available as a pip-installable package.

pip install retire

Basic Usage

from retire import Retire, Explore

# Load data and create analysis objects
retire_obj = Retire()
explore = Explore(retire_obj.graph, retire_obj.raw_df)

# Visualize the network
fig, ax = explore.drawGraph(col='ret_STATUS')

# Create geographic map
fig, ax = explore.drawMap()

# Get manuscript results
group_analysis = retire_obj.get_group_report()
explanations = retire_obj.get_target_explanations()

Documentation

See the full documentation for detailed usage instructions:

• Usage Guide - Step-by-step tutorial
• Data Sources - Available datasets
• Visualization Methods - Plotting capabilities
• Configuration - Customization options

API Overview

Main Classes

Retire - Main analysis class with data access and manuscript results Explore - Visualization toolkit for networks and geographic data

Data Loading

from retire.data import load_dataset, load_clean_dataset, load_projection, load_graph

Development

Running Tests

pytest

Contributing

This is a v0 WIP release. When contributing:

1. Test Coverage: Write tests for new functionality
2. Documentation: Update docs for API changes
3. Code Style: Follow existing patterns and conventions

License

This project is licensed under the BSD 3-Clause License - see the LICENSE.md file for details.

Citation

If you use this package in your research, please cite:

@article{retire2025,
  title={Strategies to Accelerate US Coal Power Phaseout Using Contextual Retirement Vulnerabilities},
  author={Sidney Gathrid*, Jeremy Wayland*, Stuart Wayland,Ranjit Deshmukh,Grace Wu},
  journal={Nature Energy},
  year={2025},
}

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Note: This package provides data and analysis tools for research purposes. Retirement strategies should be considered within broader energy policy and environmental justice contexts.