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Datasets / Seatbelt and helmet use in road crash casualties, Queensland / 2026-04-24

Seatbelt and helmet use in road crash casualties, Queensland, version 2026-04-24

latest
As at 30 June 2025Rows 42,787Fields 8Fetched 24 September 2026Source SHA-256 b017bdbd75dae6f6…

This version is kept for as long as this site exists, and its URL can be cited. Its files change only for the reasons the terms give, and each change is recorded in its notes. The publisher's file is here as source.csv, byte for byte.

About this version

Files rebuilt on 25 September 2026 so every one carries the operator and a ready-made cite string in its provenance header, and to add the Excel, Arrow, GeoPackage, gzipped CSV, SQL and CSVW files. Rows unchanged.

Files

  • data.arrow900 KB Arrow: Arrow IPC file (Feather v2), zstd compressed, with the provenance in the schema metadata. Memory-maps in pyarrow, Polars, Arrow JS and R without parsing.
  • data.csv3.9 MB CSV: UTF-8 without a byte-order mark, RFC 4180 quoting, one header row using the normalised field names. Opens in Excel, Numbers and Sheets.
  • data.csv-metadata.json3.4 KB
  • data.csv.gz193 KB CSV (gzip): The same CSV, gzipped, at about a tenth of the size. curl, pandas, DuckDB and R read it directly.
  • data.duckdb DuckDB: One DuckDB database with a records table of typed columns, a fields table and a publicdata metadata table. It attaches read-only over HTTPS, so DuckDB, Python and R can query it without downloading it.
  • data.json11 MB JSON: One object with a publicdata header (publisher, licence, attribution, version, source hash), a fields list and a records array of 42,787 objects with typed values. Blank cells are null.
  • data.ndjson11 MB NDJSON: The first line is the provenance header, then one JSON object per line. For streaming and for tools that read line by line.
  • data.parquet64 KB Parquet: Columnar and typed. The smallest download and the fastest to query. Reads directly in DuckDB, pandas, Polars, Arrow and Spark. The provenance header is in the file metadata.
  • data.sqlite7.2 MB SQLite: One database with a records table, a fields table and a publicdata metadata table. Open it with any SQLite client.
  • data.xlsx1.3 MB Excel: One workbook with a records sheet of 42,787 typed rows, a fields sheet and a publicdata sheet with the provenance. Dates are real Excel dates. Opens in Excel, Numbers, LibreOffice and Sheets.
  • manifest.json1.7 KB
  • schema.json1.7 KB
  • schema.sql1.9 KB
  • source.csv3.4 MB

SHA256SUMS holds the SHA-256 of every file in this version under the name it downloads as. Check what you downloaded with sha256sum -c --ignore-missing SHA256SUMS in the same folder. On a Mac, use shasum -a 256 -c --ignore-missing SHA256SUMS. Each list is signed by the deploy that wrote it: gh attestation verify SHA256SUMS --repo National-Digital/publicdata.au --source-ref refs/heads/main shows it came from this project's main branch.

Smaller files by field: by/crash_year/.

Attribution the licence asks for

Department of Transport and Main Roads, Queensland Government, Crash data from Queensland roads, sourced 24 September 2026, https://www.data.qld.gov.au/dataset/crash-data-from-queensland-roads, licensed under CC BY 4.0.

Provenance

Fetched from www.data.qld.gov.au on 24 September 2026. The portal listed the licence as Creative Commons Attribution 4.0 at that moment. manifest.json has every detail.

05k10k15k20k2001 Fatality: 2722001 Hospitalised: 4,8832001 Medically treated: 7,5482001 Minor injury: 4,6652002 Fatality: 2852002 Hospitalised: 5,1812002 Medically treated: 7,3482002 Minor injury: 4,6182003 Fatality: 2602003 Hospitalised: 5,3752003 Medically treated: 7,0832003 Minor injury: 4,52620032004 Fatality: 2762004 Hospitalised: 5,8212004 Medically treated: 7,0952004 Minor injury: 4,4362005 Fatality: 2912005 Hospitalised: 5,8762005 Medically treated: 7,0352005 Minor injury: 4,2452006 Fatality: 2892006 Hospitalised: 5,5002006 Medically treated: 7,1302006 Minor injury: 4,77520062007 Fatality: 3182007 Hospitalised: 5,6212007 Medically treated: 7,3132007 Minor injury: 5,9582008 Fatality: 2962008 Hospitalised: 6,4122008 Medically treated: 7,7302008 Minor injury: 5,0332009 Fatality: 2912009 Hospitalised: 6,2472009 Medically treated: 7,6672009 Minor injury: 3,99120092010 Fatality: 2212010 Hospitalised: 6,0792010 Medically treated: 7,0302010 Minor injury: 3,7762011 Fatality: 2352011 Hospitalised: 5,9712011 Medically treated: 6,6052011 Minor injury: 3,3662012 Fatality: 2532012 Hospitalised: 6,1502012 Medically treated: 6,9532012 Minor injury: 2,96520122013 Fatality: 2502013 Hospitalised: 6,5172013 Medically treated: 7,0722013 Minor injury: 2,4112014 Fatality: 2042014 Hospitalised: 6,2502014 Medically treated: 7,0022014 Minor injury: 2,5642015 Fatality: 2222015 Hospitalised: 5,8242015 Medically treated: 7,4782015 Minor injury: 1,98720152016 Fatality: 2142016 Hospitalised: 5,9212016 Medically treated: 7,4822016 Minor injury: 2,3472017 Fatality: 2102017 Hospitalised: 6,1432017 Medically treated: 6,7252017 Minor injury: 3,0632018 Fatality: 2092018 Hospitalised: 6,4702018 Medically treated: 6,6742018 Minor injury: 3,27920182019 Fatality: 2032019 Hospitalised: 6,6672019 Medically treated: 6,4912019 Minor injury: 3,1492020 Fatality: 2452020 Hospitalised: 6,6862020 Medically treated: 5,5902020 Minor injury: 2,9742021 Fatality: 2552021 Hospitalised: 7,4872021 Medically treated: 6,1252021 Minor injury: 3,47820212022 Fatality: 2682022 Hospitalised: 7,1982022 Medically treated: 5,6202022 Minor injury: 3,5962023 Fatality: 2472023 Hospitalised: 7,6272023 Medically treated: 5,5732023 Minor injury: 3,6022024 Fatality: 2612024 Hospitalised: 7,9472024 Medically treated: 5,3872024 Minor injury: 4,0342024
FatalityHospitalisedMedically treatedMinor injury
Casualties per year by severity, 2001 to 2024. 2025 is not drawn because the file runs to 30 June 2025. A sum of the casualties column in this version, worked out in the build.
Change from the version before

First version followed here.

When the publisher releases again, this panel shows rows added, removed and changed by crash_year, crash_police_region, casualty_severity, casualty_age_group, casualty_gender, casualty_road_user_type, casualty_restraint_helmet_use, with a link to the diff file.