poliscipy 0.1.0

A Python package for political science data visualization.

PoliSciPy

PoliSciPy is an open-source Python library that makes it easy to generate electoral maps and explore political data with just a few lines of code. The library is designed for fast experimentation, clear visualizations, and flexible customization, whether you’re analyzing results, presenting findings, or exploring historical trends.

Key Features

• Visualize Electoral Maps: Create U.S. electoral college maps with state labels, electoral votes, and party colors.
• Customize Plots: Adjust figure size, title, edge colors, label colors, and other visual elements for customized plots.
• Flexible Data Handling: Easily merge your own election results (current, historical, or hypothetical) with the map data for visualization.

Example: Figure with results from the 2024 U.S. election.

Installation

PoliSciPy requires Python 3.x and can be installed using pip:

pip install poliscipy

PoliSciPy is also available on conda via:

conda install -c conda-forge poliscipy

Dependencies: Note that PoliSciPy requires GeoPandas, matplotlib, and Pandas

Quickstart and Example

Creating electoral college maps using PoliSciPy can be done in only three simple steps:

1. Load the GeoDataFrame that contains the electoral college geospatial data
2. Load and merge the specific data you'd like to plot with the GeoDataFrame
3. Call the plot_electoral_map() function, passing in your GeoDataFrame and the target column for plotting

Below is an example of how to use PoliSciPy to visualize the 2024 U.S. electoral college map shown above.

import poliscipy

from poliscipy.shapefile_utils import load_shapefile
from poliscipy.plot import plot_electoral_map

# Load in GeoDataFrame containing U.S. electoral college geospatial data
gdf = load_shapefile()

# Create a dictionary with the data to plot
winning_party = {
    'AL': 'Republican','AK': 'Republican','AZ': 'Republican','AR': 'Republican', ...
}

# Merge your data with the gdf and fill any missing data with 'No Data'
gdf['winning_party'] = gdf['STUSPS'].map(winning_party).fillna('No Data')

# Add the number of electors that voted for the other candidate
gdf.loc[38, 'defectors'] = 1 # maine
gdf.loc[10, 'defectors'] = 1 # nebraska

# Set the political party for each of the congressional district winners
gdf.loc[38, 'defector_party'] = 'Republican'
gdf.loc[10, 'defector_party'] = 'Democrat'

# Plot the electoral college map for the year 2024
plot_electoral_map(gdf, column='winning_party', title='2024 U.S. Electoral College Map')

Documentation

Complete documentation for PoliSciPy can be found here.

Contributing

PoliSciPy welcomes contributions! Please see the CONTRIBUTING.md for guidelines on how to get involved.

Citation

If you find PoliSciPy useful in your research, academic projects, or software, please cite it using the CITATION.cff file located in the root directory of this repository.