publicdata.auby National Digital publicdata.au on GitHub
Datasets / Road casualties, Queensland / 2026-04-24

Road casualties, Queensland, version 2026-04-24

latest
As at 30 June 2025Rows 38,893Fields 7Fetched 24 September 2026Source SHA-256 bc9de78b77cc67ba…

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.arrow820 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.csv2.6 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.json3.0 KB
  • data.csv.gz220 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.json8.0 MB JSON: One object with a publicdata header (publisher, licence, attribution, version, source hash), a fields list and a records array of 38,893 objects with typed values. Blank cells are null.
  • data.ndjson8.0 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.parquet106 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.sqlite4.8 MB SQLite: One database with a records table, a fields table and a publicdata metadata table. Open it with any SQLite client.
  • data.xlsx1.1 MB Excel: One workbook with a records sheet of 38,893 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.json1.6 KB
  • schema.json1.4 KB
  • schema.sql1.5 KB
  • source.csv2.3 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.

05k10k15k20k25k2001 Fatality: 3242001 Hospitalised: 5,3092001 Medically treated: 7,8932001 Minor injury: 4,8352002 Fatality: 3222002 Hospitalised: 5,6002002 Medically treated: 7,6922002 Minor injury: 4,7862003 Fatality: 3102003 Hospitalised: 5,7992003 Medically treated: 7,3692003 Minor injury: 4,67120032004 Fatality: 3112004 Hospitalised: 6,2282004 Medically treated: 7,3582004 Minor injury: 4,5892005 Fatality: 3302005 Hospitalised: 6,3072005 Medically treated: 7,3012005 Minor injury: 4,3832006 Fatality: 3352006 Hospitalised: 5,8852006 Medically treated: 7,4122006 Minor injury: 4,90720062007 Fatality: 3602007 Hospitalised: 6,0542007 Medically treated: 7,5482007 Minor injury: 6,0892008 Fatality: 3282008 Hospitalised: 6,8382008 Medically treated: 8,0042008 Minor injury: 5,1502009 Fatality: 3312009 Hospitalised: 6,6742009 Medically treated: 7,9622009 Minor injury: 4,07420092010 Fatality: 2492010 Hospitalised: 6,4992010 Medically treated: 7,2932010 Minor injury: 3,8932011 Fatality: 2692011 Hospitalised: 6,3882011 Medically treated: 6,9022011 Minor injury: 3,4372012 Fatality: 2802012 Hospitalised: 6,5292012 Medically treated: 7,2152012 Minor injury: 3,04120122013 Fatality: 2712013 Hospitalised: 6,8982013 Medically treated: 7,3222013 Minor injury: 2,4642014 Fatality: 2232014 Hospitalised: 6,6302014 Medically treated: 7,2212014 Minor injury: 2,6272015 Fatality: 2442015 Hospitalised: 6,2012015 Medically treated: 7,7342015 Minor injury: 2,02920152016 Fatality: 2512016 Hospitalised: 6,3282016 Medically treated: 7,7032016 Minor injury: 2,4072017 Fatality: 2462017 Hospitalised: 6,5182017 Medically treated: 6,9302017 Minor injury: 3,1452018 Fatality: 2442018 Hospitalised: 6,8262018 Medically treated: 6,8402018 Minor injury: 3,35120182019 Fatality: 2222019 Hospitalised: 7,0202019 Medically treated: 6,7132019 Minor injury: 3,2292020 Fatality: 2782020 Hospitalised: 7,0152020 Medically treated: 5,7492020 Minor injury: 3,0292021 Fatality: 2752021 Hospitalised: 7,9092021 Medically treated: 6,2892021 Minor injury: 3,56620212022 Fatality: 2962022 Hospitalised: 7,6732022 Medically treated: 5,8382022 Minor injury: 3,6902023 Fatality: 2732023 Hospitalised: 8,2562023 Medically treated: 5,8502023 Minor injury: 3,7462024 Fatality: 3022024 Hospitalised: 8,6412024 Medically treated: 5,6812024 Minor injury: 4,2532024
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, with a link to the diff file.