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Published September 19, 2025 | Version 2025.4

Fatality Analysis Reporting System (FARS) Processed Data – rfars

  • 1. toXcel LLC

Description

The Fatality Analysis Reporting System (FARS) is a nationwide census of all U.S. motor vehicle crashes resulting in a fatality, maintained by the National Highway Traffic Safety Administration (NHTSA). While the raw FARS data are publicly available, they are distributed in formats that require significant preprocessing before analysis. This dataset provides a processed version of the FARS database (2014-2023), optimized for immediate use in R, Python, Excel, and other modern data tools. It was prepared by the rfars R package, enabling researchers, policymakers, and educators to access and analyze fatal crash data more efficiently and reproducibly.

This dataset is provided in three different file formats to support a wide range of users and analysis environments:

  • CSV (.csv) - a plain text format, with each of the five tables saved separately. These files are the most universally compatible and can be opened directly in Excel, though they are larger.
  • Parquet (.parquet) - a modern, compressed, cross-platform columnar format. Each of the five tables is provided separately (fars_accident.parquet, fars_vehicle.parquet, etc.). This version is recommended for Python, SQL, and advanced R users, as it is smaller than CSV and loads quickly in most data science environments.
  • RDS (.rds) - a native R format containing the full dataset as a list of five related tables (accident, vehicle, person, drugs, distract). This version is recommended for R users, since it can be loaded in one step with readRDS() and preserves all variable types exactly as processed.

Notes

Version 2025.4 adds the codebooks with definitions.

Files

fars_codebook.csv

Files (3.0 GB)

Name Size
md5:6a3ed3ce694cd6894509136bfb55875d
87.4 MB Download
md5:89169889fa779125f8faf2d3d99b1fbd
9.0 MB Preview Download
md5:41215e6c2d98d830426bdcae5a0908aa
204.9 kB Download
md5:7386a865e98e2d30f93c35824a3b4aca
76.7 MB Preview Download
md5:192c822ebf0cc0ca55b1f5b010f15c36
4.3 MB Download
md5:cb02b746ab9bb6f4594ab5f14179b83c
2.2 GB Preview Download
md5:e7c71d1d2f22c11968a49a464104e6f8
78.8 MB Download
md5:da4800fc785d2ff645ef2610b7f0c0ca
17.7 MB Preview Download
md5:1a51a9d0a8c268f0d64d1c64f3639e0c
1.2 MB Download
md5:a11bf5c4764c222042378429f7adf1f2
266.1 MB Preview Download
md5:e6e6ef0b47cf85c027efd88ebff796cc
8.5 MB Download
md5:263c55f72995cfe221838c5e8b45a588
239.2 MB Preview Download
md5:650e9fb8a66614c0a344ffd2594fcae8
11.2 MB Download

Additional details

Related works

Dates

Submitted
2025-09

Software

Repository URL
https://github.com/s87jackson/rfars/
Programming language
R
Development Status
Active