PolaPy

PolaPy (Polarization for Python) is a collection of algorithmic implementations of polarization and electoral competition metrics in Python.

Features

• 📊 Polarization Metrics: Esteban-Ray, Reynal-Querol, Wang-Tsui, and Electoral Divisiveness
• 🗳️ Electoral Competition: Blais-Lago, Grofman-Selb, and Laakso-Taagepera indices
• 📈 Electoral Systems: D'Hondt method and proportional allocation
• 🐼 Pandas Integration: Works seamlessly with DataFrames

Installation

pip install polapy

Quick Start

Polarization Metrics

import pandas as pd
from polapy.polarization import esteban_ray, reynal_querol, electoral_divisiveness

# Esteban-Ray polarization
df = pd.DataFrame({'pi': [0.5, 0.5], 'y': [1, 2]})
value = esteban_ray(df, alpha=0.5)

# Reynal-Querol polarization
df = pd.DataFrame({'rate': [0.4, 0.3, 0.2, 0.1]})
value = reynal_querol(df)

# Electoral Divisiveness
df = pd.DataFrame({
    'unit': ['A', 'A', 'B', 'B'],
    'candidate': ['X', 'Y', 'X', 'Y'],
    'votes': [100, 50, 60, 90]
})
value, details = electoral_divisiveness(df)

Electoral Competition

from polapy.competitiveness import blais_lago, grofman_selb, laackso_taagepera

# Effective Number of Parties
df = pd.DataFrame({'share': [0.4, 0.35, 0.25]})
enp = laackso_taagepera(df)

# Blais-Lago competition index
df = pd.DataFrame({'party': ['A', 'B', 'C'], 'votes': [5000, 3000, 2000]})
value, details = blais_lago(df, n_seats=5)

Available Metrics

Module	Metric	Reference
polarization	electoral_divisiveness	Navarrete et al. (2023)
polarization	esteban_ray	Esteban & Ray (1994)
polarization	reynal_querol	Reynal-Querol (2002)
polarization	wang_tsui	Wang & Tsui (2000)
competitiveness	blais_lago	Blais & Lago (2009)
competitiveness	grofman_selb	Grofman & Selb (2009)
competitiveness	laackso_taagepera	Laakso & Taagepera (1979)
aggregate	dhondt	D'Hondt/Jefferson method
aggregate	proportional	Largest Remainder Method

Requirements

• Python ≥ 3.7
• numpy
• pandas
• scipy

About

PolaPy is developed and maintained by researchers at the University of Concepción (Chile). For questions, issues, or contributions, visit our GitHub repository.

License

MIT License - see LICENSE.md for details.