electiondata

electiondata: a Python package for consolidating, checking, analyzing, visualizing and exporting election results - Published in JOSS (2022)

https://github.com/electiondataanalysis/electiondata

Science Score: 95.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 1 DOI reference(s) in JOSS metadata
  • Academic publication links
  • Committers with academic emails
    2 of 9 committers (22.2%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

common-data-format election election-data

Scientific Fields

Mathematics Computer Science - 84% confidence
Last synced: 6 months ago · JSON representation

Repository

Tools for consolidation and analysis of raw election results from the most reliable sources -- the election agencies themselves.

Basic Info
  • Host: GitHub
  • Owner: ElectionDataAnalysis
  • License: other
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 48.6 MB
Statistics
  • Stars: 21
  • Watchers: 2
  • Forks: 5
  • Open Issues: 54
  • Releases: 3
Topics
common-data-format election election-data
Created over 5 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Contributing License Code of conduct

README.md

CII Best Practices

Overview

This repository provides tools for consolidation and analysis of raw election results from the most reliable sources -- the election agencies themselves. * Consolidation: take as input election results files from a wide variety of sources and load the data into a relational database * Export: create consistent-format export files of results sets rolled up to any desired intermediate geography * tabular (tab-separated text) * xml (following NIST Election Results Reporting Common Data Format V2) * json (following NIST Election Results Reporting Common Data Format V2) * Analysis: * Curates one-county outliers of interest * Calculates difference-in-difference for results available by vote type * Visualization: * Scatter plots * Bar charts

Target Audience

This system is intended to be of use to news media, campaigns, election officials, students of politics and elections, and anyone else who is interested in assembling and understanding election results. If you have ideas for using this system or if you would like to stay updated on the progress of this project, we'd like to hear from you.

How to use the app

See documentation directory, which includes * for users * Installation instructions * Instructions for a sample dataloading session * Detailed User Guide

How to Contribute Code

See CONTRIBUTING.MD.

Contributors

  • Stephanie Singer, Hatfield School of Government (Portland State University), former Chair, Philadelphia County Board of Elections
  • Janaki Raghuram Srungavarapu, Hatfield School of Government (Portland State University)
  • Eric Tsai, Hatfield School of Government (Portland State University)
  • Todd Graham, Hatfield School of Government (Portland State University)
  • Bryan Loy
  • Jon Wolgamott
  • Elliot Meyerson

Copyright

Copyright (c) Portland State University 2021

Funding

Funding provided October 2019 - November 2021 by the National Science Foundation * Award #1936809, "EAGER: Data Science for Election Verification" * Award #2027089, "RAPID: Election Result Anomaly Detection for 2020" Data collection and consolidation for the 2020 US General Election funded in part by the Verified Voting Foundation.

License

See LICENSE.md

JOSS Publication

electiondata: a Python package for consolidating, checking, analyzing, visualizing and exporting election results
Published
January 05, 2022
Volume 7, Issue 69, Page 3739
Authors
Stephanie Frank Singer ORCID
Hatfield School of Government, Portland State University
Eric M. Tsai
Independent Researcher
Editor
Andrew Stewart ORCID
Tags
elections voting data consolidation outliers

GitHub Events

Total
  • Watch event: 1
Last Year
  • Watch event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 3,736
  • Total Committers: 9
  • Avg Commits per committer: 415.111
  • Development Distribution Score (DDS): 0.226
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Stephanie Singer 1****3 2,893
Eric Tsai e****i@t****m 444
Jon Wolgamott J****t@g****m 158
Raghu Srungavarapu j****2@p****u 124
ekmeyerson e****n@g****m 66
Nick Hershman n****n@g****m 18
Todd Graham t****1@g****m 15
Bryan Loy l****d@g****m 12
Stephanie Singer s****3@c****u 6
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 52
  • Total pull requests: 48
  • Average time to close issues: 15 days
  • Average time to close pull requests: 2 days
  • Total issue authors: 2
  • Total pull request authors: 2
  • Average comments per issue: 0.56
  • Average comments per pull request: 0.06
  • Merged pull requests: 47
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • sfsinger19103 (46)
  • toddgraham121 (6)
Pull Request Authors
  • sfsinger19103 (47)
  • ajstewartlang (1)
Top Labels
Issue Labels
enhancement (8) documentation (6) user convenience (5) bug (2) good first issue (2) technical debt (1) high-priority (1)
Pull Request Labels
do not merge yet (1)

Dependencies

requirements.txt pypi
  • SQLAlchemy ==1.3.12
  • configparser *
  • dicttoxml ==1.7.4
  • electiondata *
  • lxml ==4.6.3
  • matplotlib ==3.1.2
  • numpy ==1.21.4
  • openpyxl ==3.0.6
  • pandas ==1.3.2
  • path ==15.0.1
  • plotly ==4.12.0
  • psutil ==5.8.0
  • psycopg2 ==2.8.6
  • pytest ==6.1.1
  • python-slugify *
  • requests ==2.25.1
  • scipy ==1.6.3
  • setuptools *
  • xlrd >=1.0.0
setup.py pypi
  • sqlalchemy *