One month from July 1997, with the number of offences reported to the Queensland Police Service across the state in that month, one column per offence category. Some columns, such as Assault and Offences Against the Person, are groups that include other categories, so adding every column counts some offences more than once.

Is this the number of crimes committed?

It is the number of offences the police recorded as reported. An offence nobody reported is not counted, and police activity drives some categories, such as drug and good order offences.

Why are some newer categories zero in early years?

Categories such as Coercive Control, Voluntary Assisted Dying and E-mobility began when the law created them, and the publisher writes 0 for the months before.

Datasets / Queensland / QPS

Reported offences by month, Queensland, from July 1997

Name: Reported offences by month, Queensland, from July 1997
Creator: Queensland Police Service
Published: 2026-09-11
License: https://creativecommons.org/licenses/by/4.0/

live

Publisher Queensland Police ServiceUpdated monthlyLicence CC BY 4.0Latest 2026-09-11Rows 350Fields 93

Monthly counts of offences reported to the Queensland Police Service for the whole state from July 1997, one row per month. Each of about 90 columns is an offence category or a group of categories, from homicide and assault to fraud, drug, traffic and good order offences. The publisher updates the file each month.

Also called: QPS reported offences monthly, Queensland offence numbers, QLD crime statistics, Queensland crime rates over time.

Before you use it

What is in each row?: One month from July 1997, with the number of offences reported to the Queensland Police Service across the state in that month, one column per offence category. Some columns, such as Assault and Offences Against the Person, are groups that include other categories, so adding every column counts some offences more than once.
Is this the number of crimes committed?: It is the number of offences the police recorded as reported. An offence nobody reported is not counted, and police activity drives some categories, such as drug and good order offences.
Why are some newer categories zero in early years?: Categories such as Coercive Control, Voluntary Assisted Dying and E-mobility began when the law created them, and the publisher writes 0 for the months before.

350months

1998 to 2025years drawn

93fields

9formats

1version

Offences against the person reported per year, 1998 to 2025. Rows where month is at least 1998-01-01 are drawn. 2026 is not drawn because the rows run to 1 August 2026. The figure is a sum of the offences against the person column from version 2026-09-11, worked out in the build. Nothing else is added.

Open this dashboard in the explorer Download Query

Made for agents

Connect your AI agent

Any agent that connects to publicdata.au/mcp can find this dataset, read its 93 fields, count and filter across all 350 rows and diff its versions. Every answer names the version and carries QPS's attribution. No key.

Then ask it: What does Reported offences by month, Queensland, from July 1997 hold, and what changed in the newest version?

claude mcp add --transport http publicdata https://publicdata.au/mcp

One command. No key, no account, no sign-up.

https://publicdata.au/mcp

Streamable HTTP. Cursor, VS Code or any client that connects to a remote MCP server.

Using https://publicdata.au/llms.txt, how many people died on Queensland roads in 2025, by month?

For an assistant that reads the web and has no connector.

ExploreChart every row in your browser

The dashboard above, live. Click to filter, add panels, share a link or embed a frame.

Query APIFilter and count from a URL

aggregate?group=month&metric=sum.offences_against_the_person&month=eq.2026-08-01

Offences against the person reported in the newest month: 6,874 2026-08-01.

Download it as Excel, CSV, JSON and 6 more formats

Pick a format and a version. Excel is picked first because it opens in the tools most offices have. The URL is yours to keep. A dated version never changes.

Format

Version "Latest" redirects to the newest version and will change when the publisher releases again. A dated version never changes.

https://publicdata.au/d/qld-offences-monthly/latest/data.xlsx

Download

In your own tools

Use it in Excel, R, Python and more

Excel and Power BI read the CSV from its address and refresh from it. The R and Python packages take any dataset on this site by its slug, so a new dataset needs no new release. The DuckDB file attaches read-only over HTTPS, and a query reads only the blocks it touches.

The dated URL in the code never changes. https://publicdata.au/d/qld-offences-monthly/latest/ redirects to the newest version.

https://publicdata.au/d/qld-offences-monthly/latest/data.csv

In Excel choose Data, then From Web, and paste this address. Excel keeps it, so Refresh All reads the newest version. A sheet holds about a million rows; past that, load the query to the Data Model.

https://publicdata.au/d/qld-offences-monthly/latest/data.csv

In Power BI Desktop choose Get data, then Web, paste this address and choose Anonymous when asked how to sign in. A scheduled refresh reads the same address, so the report follows each new version.

library(publicdataau)
df <- pd_read("qld-offences-monthly")
pd_attribution(df)

install.packages("publicdataau"). pd_read() fetches the version's Parquet file; pd_rows() and pd_aggregate() ask the query API instead, and pd_connect() attaches the DuckDB file.

import publicdata_au as pd_au
df = pd_au.read("qld-offences-monthly")
df.attrs["publicdata"]["attribution"]

pip install "publicdata-au[pandas]". read() fetches the version's Parquet file; rows() and aggregate() ask the query API, and connect() attaches the DuckDB file.

INSTALL httpfs; LOAD httpfs;
ATTACH 'https://publicdata.au/d/qld-offences-monthly/v/2026-09-11/data.duckdb' AS qld_offences_monthly (READ_ONLY);
SELECT month, count(*) FROM qld_offences_monthly.records GROUP BY 1 ORDER BY 2 DESC;

The DuckDB file attaches read-only over HTTPS and only the blocks a query touches are read. Parquet works the same way: FROM read_parquet(url).

const res = await fetch("https://publicdata.au/api/v1/datasets/qld-offences-monthly/aggregate?group=month&metric=sum.offences_against_the_person&month=eq.2026-08-01");
const { rows, publicdata } = await res.json();
console.log(rows, publicdata.attribution);

The query API answers a page on any site as well as Node, with no key. It returns the rows and the attribution the licence asks for.

What is in it

Column names are made snake_case and the publisher's original header is kept beside each one. Blank cells are null. Nothing is added, removed, ranked or summarised. Cells were typed and headers were made snake_case. The publisher's header is kept beside every field in schema.json. Rows were left alone.

Field	Type	Publisher's header	Note
month	date	Month Year	The month the offences were reported, published as a month and two-digit year such as JUL97 and read as the first day of that month.
homicide_murder	integer	Homicide (Murder)
other_homicide	integer	Other Homicide
attempted_murder	integer	Attempted Murder
conspiracy_to_murder	integer	Conspiracy to Murder
manslaughter_excl_by_driving	integer	Manslaughter (excl. by driving)
driving_causing_death	integer	Driving Causing Death
manslaughter_unlawful_striking_causing_death	integer	Manslaughter Unlawful Striking Causing Death
assault	integer	Assault
grievous_assault	integer	Grievous Assault
serious_assault	integer	Serious Assault
serious_assault_other	integer	Serious Assault (Other)
common_assault	integer	Common Assault'	The publisher's header ends in a stray apostrophe, Common Assault', kept as the source name.
sexual_offences	integer	Sexual Offences
rape_and_attempted_rape	integer	Rape and Attempted Rape
other_sexual_offences	integer	Other Sexual Offences
robbery	integer	Robbery
armed_robbery	integer	Armed Robbery
unarmed_robbery	integer	Unarmed Robbery
other_offences_against_the_person	integer	Other Offences Against the Person
kidnapping_abduction_etc	integer	Kidnapping & Abduction etc.
coercive_control	integer	Coercive Control
extortion	integer	Extortion
stalking	integer	Stalking
life_endangering_acts	integer	Life Endangering Acts
voluntary_assisted_dying	integer	Voluntary Assisted Dying
other_miscellaneous	integer	Other Miscellaneous
offences_against_the_person	integer	Offences Against the Person
unlawful_entry	integer	Unlawful Entry
unlawful_entry_with_intent_dwelling	integer	Unlawful Entry With Intent - Dwelling
unlawful_entry_without_violence_dwelling	integer	Unlawful Entry Without Violence - Dwelling
unlawful_entry_with_violence_dwelling	integer	Unlawful Entry With Violence - Dwelling
unlawful_entry_with_intent_shop	integer	Unlawful Entry With Intent - Shop
unlawful_entry_with_intent_other	integer	Unlawful Entry With Intent - Other
arson	integer	Arson
other_property_damage	integer	Other Property Damage
unlawful_use_of_motor_vehicle	integer	Unlawful Use of Motor Vehicle
other_theft_excl_unlawful_entry	integer	Other Theft (excl. Unlawful Entry)
stealing_from_dwellings	integer	Stealing from Dwellings
shop_stealing	integer	Shop Stealing
vehicles_steal_from_enter_with_intent	integer	Vehicles (steal from/enter with intent)
other_stealing	integer	Other Stealing
fraud	integer	Fraud
fraud_by_computer	integer	Fraud by Computer
fraud_by_cheque	integer	Fraud by Cheque
fraud_by_credit_card	integer	Fraud by Credit Card
identity_fraud	integer	Identity Fraud
other_fraud	integer	Other Fraud
handling_stolen_goods	integer	Handling Stolen Goods
possess_property_suspected_stolen	integer	Possess Property Suspected Stolen
receiving_stolen_property	integer	Receiving Stolen Property
possess_etc_tainted_property	integer	Possess etc. Tainted Property
other_handling_stolen_goods	integer	Other Handling Stolen Goods
offences_against_property	integer	Offences Against Property
drug_offences	integer	Drug Offences
trafficking_drugs	integer	Trafficking Drugs
possess_drugs	integer	Possess Drugs
produce_drugs	integer	Produce Drugs
sell_supply_drugs	integer	Sell Supply Drugs
other_drug_offences	integer	Other Drug Offences
prostitution_offences	integer	Prostitution Offences
found_in_places_used_for_purpose_of_prostitution_offences	integer	Found in Places Used for Purpose of Prostitution Offences
have_interest_in_premises_used_for_prostitution_offences	integer	Have Interest in Premises Used for Prostitution Offences
knowingly_participate_in_provision_prostitution_offences	integer	Knowingly Participate in Provision Prostitution Offences
public_soliciting	integer	Public Soliciting
procuring_prostitution	integer	Procuring Prostitution
permit_minor_to_be_at_a_place_used_for_prostitution_offences	integer	Permit Minor to be at a Place Used for Prostitution Offences
advertising_prostitution	integer	Advertising Prostitution
other_prostitution_offences	integer	Other Prostitution Offences
liquor_excl_drunkenness	integer	Liquor (excl. Drunkenness)
gaming_racing_betting_offences	integer	Gaming Racing & Betting Offences
breach_domestic_violence_protection_order	integer	Breach Domestic Violence Protection Order
trespassing_and_vagrancy	integer	Trespassing and Vagrancy
weapons_act_offences	integer	Weapons Act Offences
unlawful_possess_concealable_firearm	integer	Unlawful Possess Concealable Firearm
unlawful_possess_firearm_other	integer	Unlawful Possess Firearm - Other
bomb_possess_and_or_use_of	integer	Bomb Possess and/or use of
possess_and_or_use_other_weapons_restricted_items	integer	Possess and/or use other weapons; restricted items
weapons_act_offences_other	integer	Weapons Act Offences - Other
good_order_offences	integer	Good Order Offences
disobey_move_on_direction	integer	Disobey Move-on Direction
resist_incite_hinder_obstruct_police	integer	Resist Incite Hinder Obstruct Police
fare_evasion	integer	Fare Evasion
public_nuisance	integer	Public Nuisance
stock_related_offences	integer	Stock Related Offences
traffic_and_related_offences	integer	Traffic and Related Offences
dangerous_operation_of_a_vehicle	integer	Dangerous Operation of a Vehicle
drink_driving	integer	Drink Driving
disqualified_driving	integer	Disqualified Driving
interfere_with_mechanism_of_motor_vehicle	integer	Interfere with Mechanism of Motor Vehicle
e_mobility	integer	E-mobility
miscellaneous_offences	integer	Miscellaneous Offences
other_offences	integer	Other Offences

Download this table as a data dictionary (Excel), or read it as a Frictionless Table Schema at schema.json. The key is month.

A sample of 10 rows

From the latest version, newest first by month, then in the publisher's order, with every field. A blank cell is shown as null.

month	homicide_murder	other_homicide	attempted_murder	manslaughter_excl_by_driving	driving_causing_death	manslaughter_unlawful_striking_causing_death	assault	grievous_assault	serious_assault	serious_assault_other	common_assault	sexual_offences	rape_and_attempted_rape	other_sexual_offences	robbery	armed_robbery	unarmed_robbery	other_offences_against_the_person	kidnapping_abduction_etc	coercive_control	extortion	stalking	life_endangering_acts	other_miscellaneous	offences_against_the_person	unlawful_entry	unlawful_entry_with_intent_dwelling	unlawful_entry_without_violence_dwelling	unlawful_entry_with_violence_dwelling	unlawful_entry_with_intent_shop	unlawful_entry_with_intent_other	arson	other_property_damage	unlawful_use_of_motor_vehicle	other_theft_excl_unlawful_entry	stealing_from_dwellings	shop_stealing	vehicles_steal_from_enter_with_intent	other_stealing	fraud	fraud_by_computer	fraud_by_cheque	fraud_by_credit_card	identity_fraud	other_fraud	handling_stolen_goods	possess_property_suspected_stolen	receiving_stolen_property	possess_etc_tainted_property	other_handling_stolen_goods	offences_against_property	drug_offences	trafficking_drugs	possess_drugs	produce_drugs	sell_supply_drugs	other_drug_offences	liquor_excl_drunkenness	gaming_racing_betting_offences	breach_domestic_violence_protection_order	trespassing_and_vagrancy	weapons_act_offences	unlawful_possess_concealable_firearm	unlawful_possess_firearm_other	bomb_possess_and_or_use_of	possess_and_or_use_other_weapons_restricted_items	weapons_act_offences_other	good_order_offences	disobey_move_on_direction	resist_incite_hinder_obstruct_police	fare_evasion	public_nuisance	stock_related_offences	traffic_and_related_offences	dangerous_operation_of_a_vehicle	drink_driving	disqualified_driving	interfere_with_mechanism_of_motor_vehicle	e_mobility	miscellaneous_offences	other_offences
2026-08-01	2	3	1	1	1	0	4854	79	2101	498	2176	925	321	604	220	114	106	870	41	19	15	195	600	0	6874	2942	1647	1583	64	205	1090	112	3157	1509	12579	625	4058	2425	5471	1640	108	2	554	103	873	538	237	21	276	4	22477	9368	64	4260	42	867	4135	212	0	5836	809	1051	31	94	8	595	323	3842	64	2094	22	1662	3	4569	294	2825	1277	1	172	659	26349
2026-07-01	3	10	9	0	0	1	4854	77	1957	565	2255	927	363	564	223	116	107	889	59	37	17	190	585	1	6906	2639	1338	1280	58	232	1069	123	3210	1453	12341	637	4174	2422	5108	1646	146	0	428	79	993	641	266	29	336	10	22053	9462	50	4210	49	1006	4147	158	0	5944	774	1031	37	72	4	593	325	3760	51	2139	45	1525	0	4480	264	2637	1313	2	264	760	26369
2026-06-01	1	3	1	0	2	0	4655	91	2016	446	2102	1080	411	669	196	92	104	877	67	28	17	210	554	1	6812	2966	1546	1475	71	226	1194	113	3267	1446	12721	586	4107	2533	5495	1957	90	1	646	119	1101	569	281	39	242	7	23039	8470	112	3716	43	789	3810	120	0	5377	759	939	42	72	18	478	329	3624	70	2034	45	1475	5	3920	329	2645	944	2	0	799	24013
2026-05-01	2	11	9	0	2	0	4973	76	2136	504	2257	1090	431	659	201	86	115	896	64	25	33	199	575	0	7173	3234	1736	1674	62	249	1249	122	3385	1640	13108	641	3932	2734	5801	1312	51	2	516	46	697	544	220	18	301	5	23345	8422	60	3835	33	816	3678	170	0	5978	732	937	29	77	4	510	317	4418	55	2685	33	1645	4	4142	340	2864	935	3	0	1052	25855
2026-04-01	1	5	1	0	4	0	5010	98	2194	523	2195	1115	447	668	237	126	111	852	61	30	8	163	590	0	7220	3276	1730	1641	89	282	1264	90	3462	1615	13212	677	3666	2743	6126	1449	58	6	677	47	661	525	257	20	242	6	23629	6743	109	2968	32	691	2943	162	0	5758	782	823	27	60	7	462	267	3616	58	2030	47	1481	15	3794	257	2644	890	3	0	599	22292
2026-03-01	6	3	2	0	1	0	5213	80	2257	551	2325	961	350	611	248	116	132	950	72	34	11	210	623	0	7381	3688	2115	2046	69	314	1259	93	3771	1756	13765	607	4074	2766	6318	1654	84	1	658	63	848	593	277	21	287	8	25320	8011	65	3466	57	933	3490	162	0	6317	851	974	21	87	8	518	340	3876	78	1986	35	1777	1	4050	277	2731	1036	6	0	921	25163
2026-02-01	1	5	2	2	1	0	4834	87	2109	496	2142	1077	411	666	193	96	97	877	54	42	12	222	547	0	6987	3078	1821	1740	81	192	1065	95	3325	1507	11340	574	3480	2189	5097	1932	55	0	971	47	859	610	271	22	314	3	21887	8327	61	3458	64	1055	3689	202	0	5878	825	865	28	70	2	464	301	3497	55	1797	50	1595	0	3705	258	2398	1047	2	0	604	23903
2026-01-01	1	7	4	0	3	0	5106	97	2164	577	2268	1071	431	640	219	106	113	874	69	29	11	200	563	2	7278	3599	2085	1984	101	248	1266	141	3768	1778	12627	676	3789	2352	5810	1884	107	1	564	57	1155	615	278	23	311	3	24412	7673	75	3412	49	789	3348	167	0	6249	872	914	24	78	5	466	341	3798	73	1897	40	1788	0	4036	275	2670	1090	1	0	553	24262
2025-12-01	5	10	9	0	1	0	5283	71	2348	546	2318	964	394	570	231	117	114	842	47	29	12	199	555	0	7335	3524	2133	2046	87	272	1119	114	3710	1811	12524	640	3583	2500	5801	1684	69	0	488	60	1067	614	261	33	316	4	23981	7616	42	3291	47	854	3382	190	0	6641	832	918	13	70	7	505	323	3471	48	1804	34	1585	2	4132	234	2830	1066	2	0	726	24528
2025-11-01	3	12	2	1	8	1	5262	104	2206	608	2344	1066	396	670	210	100	110	877	73	32	9	185	578	0	7430	3340	1952	1878	74	249	1139	112	3551	1815	12470	607	3447	2632	5784	1893	124	4	495	113	1157	670	303	23	339	5	23851	7555	46	3393	50	642	3424	213	1	6105	827	883	28	54	8	487	306	3628	50	1923	47	1608	0	4147	261	2761	1121	4	0	879	24238

The first row as JSON

As it appears in data.json.

GET https://publicdata.au/d/qld-offences-monthly/latest/data.json
{
  "month": "1997-07-01",
  "homicide_murder": 7,
  "other_homicide": 13,
  "attempted_murder": 6,
  "conspiracy_to_murder": 1,
  "manslaughter_excl_by_driving": 0,
  "driving_causing_death": 6,
  "manslaughter_unlawful_striking_causing_death": 0,
  "assault": 1241,
  "grievous_assault": 47,
  "serious_assault": 661,
  "serious_assault_other": 102,
  "common_assault": 431,
  "sexual_offences": 333,
  "rape_and_attempted_rape": 46,
  "other_sexual_offences": 287,
  "robbery": 232,
  "armed_robbery": 132,
  "unarmed_robbery": 100,
  "other_offences_against_the_person": 276,
  "kidnapping_abduction_etc": 32,
  "coercive_control": 0,
  "extortion": 4,
  "stalking": 66,
  "life_endangering_acts": 174,
  "voluntary_assisted_dying": 0,
  "other_miscellaneous": 0,
  "offences_against_the_person": 2102,
  "unlawful_entry": 6335,
  "unlawful_entry_with_intent_dwelling": 3736,
  "unlawful_entry_without_violence_dwelling": 3685,
  "unlawful_entry_with_violence_dwelling": 51,
  "unlawful_entry_with_intent_shop": 698,
  "unlawful_entry_with_intent_other": 1901,
  "arson": 155,
  "other_property_damage": 4408,
  "unlawful_use_of_motor_vehicle": 1550,
  "other_theft_excl_unlawful_entry": 7968,
  "stealing_from_dwellings": 571,
  "shop_stealing": 916,
  "vehicles_steal_from_enter_with_intent": 2517,
  "other_stealing": 3964,
  "fraud": 1920,
  "fraud_by_computer": 0,
  "fraud_by_cheque": 618,
  "fraud_by_credit_card": 263,
  "identity_fraud": 0,
  "other_fraud": 1039,
  "handling_stolen_goods": 410,
  "possess_property_suspected_stolen": 53,
  "receiving_stolen_property": 219,
  "possess_etc_tainted_property": 132,
  "other_handling_stolen_goods": 6,
  "offences_against_property": 22746,
  "drug_offences": 2950,
  "trafficking_drugs": 8,
  "possess_drugs": 1329,
  "produce_drugs": 248,
  "sell_supply_drugs": 136,
  "other_drug_offences": 1229,
  "prostitution_offences": 34,
  "found_in_places_used_for_purpose_of_prostitution_offences": 9,
  "have_interest_in_premises_used_for_prostitution_offences": 4,
  "knowingly_participate_in_provision_prostitution_offences": 3,
  "public_soliciting": 14,
  "procuring_prostitution": 2,
  "permit_minor_to_be_at_a_place_used_for_prostitution_offences": 0,
  "advertising_prostitution": 0,
  "other_prostitution_offences": 2,
  "liquor_excl_drunkenness": 99,
  "gaming_racing_betting_offences": 0,
  "breach_domestic_violence_protection_order": 366,
  "trespassing_and_vagrancy": 134,
  "weapons_act_offences": 434,
  "unlawful_possess_concealable_firearm": 15,
  "unlawful_possess_firearm_other": 161,
  "bomb_possess_and_or_use_of": 6,
  "possess_and_or_use_other_weapons_restricted_items": 45,
  "weapons_act_offences_other": 207,
  "good_order_offences": 1130,
  "disobey_move_on_direction": 0,
  "resist_incite_hinder_obstruct_police": 402,
  "fare_evasion": 85,
  "public_nuisance": 643,
  "stock_related_offences": 0,
  "traffic_and_related_offences": 1925,
  "dangerous_operation_of_a_vehicle": 86,
  "drink_driving": 1633,
  "disqualified_driving": 197,
  "interfere_with_mechanism_of_motor_vehicle": 9,
  "e_mobility": 0,
  "miscellaneous_offences": 82,
  "other_offences": 7154
}

{
  "month": "1997-07-01",
  "homicide_murder": 7,
  "other_homicide": 13,
  "attempted_murder": 6,
  "conspiracy_to_murder": 1,
  "manslaughter_excl_by_driving": 0,
  "driving_causing_death": 6,
  "manslaughter_unlawful_striking_causing_death": 0,
  "assault": 1241,
  "grievous_assault": 47,
  "serious_assault": 661,
  "serious_assault_other": 102,
  "common_assault": 431,
  "sexual_offences": 333,
  "rape_and_attempted_rape": 46,
  "other_sexual_offences": 287,
  "robbery": 232,
  "armed_robbery": 132,
  "unarmed_robbery": 100,
  "other_offences_against_the_person": 276,
  "kidnapping_abduction_etc": 32,
  "coercive_control": 0,
  "extortion": 4,
  "stalking": 66,
  "life_endangering_acts": 174,
  "voluntary_assisted_dying": 0,
  "other_miscellaneous": 0,
  "offences_against_the_person": 2102,
  "unlawful_entry": 6335,
  "unlawful_entry_with_intent_dwelling": 3736,
  "unlawful_entry_without_violence_dwelling": 3685,
  "unlawful_entry_with_violence_dwelling": 51,
  "unlawful_entry_with_intent_shop": 698,
  "unlawful_entry_with_intent_other": 1901,
  "arson": 155,
  "other_property_damage": 4408,
  "unlawful_use_of_motor_vehicle": 1550,
  "other_theft_excl_unlawful_entry": 7968,
  "stealing_from_dwellings": 571,
  "shop_stealing": 916,
  "vehicles_steal_from_enter_with_intent": 2517,
  "other_stealing": 3964,
  "fraud": 1920,
  "fraud_by_computer": 0,
  "fraud_by_cheque": 618,
  "fraud_by_credit_card": 263,
  "identity_fraud": 0,
  "other_fraud": 1039,
  "handling_stolen_goods": 410,
  "possess_property_suspected_stolen": 53,
  "receiving_stolen_property": 219,
  "possess_etc_tainted_property": 132,
  "other_handling_stolen_goods": 6,
  "offences_against_property": 22746,
  "drug_offences": 2950,
  "trafficking_drugs": 8,
  "possess_drugs": 1329,
  "produce_drugs": 248,
  "sell_supply_drugs": 136,
  "other_drug_offences": 1229,
  "prostitution_offences": 34,
  "found_in_places_used_for_purpose_of_prostitution_offences": 9,
  "have_interest_in_premises_used_for_prostitution_offences": 4,
  "knowingly_participate_in_provision_prostitution_offences": 3,
  "public_soliciting": 14,
  "procuring_prostitution": 2,
  "permit_minor_to_be_at_a_place_used_for_prostitution_offences": 0,
  "advertising_prostitution": 0,
  "other_prostitution_offences": 2,
  "liquor_excl_drunkenness": 99,
  "gaming_racing_betting_offences": 0,
  "breach_domestic_violence_protection_order": 366,
  "trespassing_and_vagrancy": 134,
  "weapons_act_offences": 434,
  "unlawful_possess_concealable_firearm": 15,
  "unlawful_possess_firearm_other": 161,
  "bomb_possess_and_or_use_of": 6,
  "possess_and_or_use_other_weapons_restricted_items": 45,
  "weapons_act_offences_other": 207,
  "good_order_offences": 1130,
  "disobey_move_on_direction": 0,
  "resist_incite_hinder_obstruct_police": 402,
  "fare_evasion": 85,
  "public_nuisance": 643,
  "stock_related_offences": 0,
  "traffic_and_related_offences": 1925,
  "dangerous_operation_of_a_vehicle": 86,
  "drink_driving": 1633,
  "disqualified_driving": 197,
  "interfere_with_mechanism_of_motor_vehicle": 9,
  "e_mobility": 0,
  "miscellaneous_offences": 82,
  "other_offences": 7154
}

Query it without downloading

The query API returns only the rows you ask for, as JSON, NDJSON or CSV, from the same typed rows as the files. It needs no key. Build a query here and run it, then copy the URL or the code into your own work.

Try rows or aggregate for this dataset. The query builder needs JavaScript.

How filters work

Each filter is field=operator.value in the query string, and every filter must match. A number or date field compares as a number or date, and a text field compares as text. Values are case-sensitive except with ilike. Prefix not. to negate a filter, as not.eq.value.

Operator	What it matches
eq.value	Equal to the value.
neq.value	Not equal to the value. A blank cell does not match.
gt.value	Greater than the value.
gte.value	Greater than or equal to the value.
lt.value	Less than the value.
lte.value	Less than or equal to the value.
like.text	Matches a pattern where * stands for any run of characters. Case-sensitive.
ilike.text	The same as like, ignoring case.
in.(a,b,c)	Equal to any value in the list. A value cannot contain a comma.
is.null	Blank in the source, or suppressed by the publisher.

Parameter	What it does
select	Fields to return, comma-separated. Every field when absent.
order	field.asc or field.desc, comma-separated. The publisher's row order when absent.
limit	Rows per page, 1 to 10,000. 100 when absent.
offset	Rows to skip. The next URL in each answer sets it for you.
group	On aggregate, fields to group by, comma-separated.
metric	On aggregate, count, sum.field, avg.field, min.field or max.field, comma-separated. count when absent.
format	json, ndjson or csv. JSON carries the provenance header, and the others carry it in response headers.

Without a version the API answers from the newest loaded version, and that answer changes when the publisher releases again. Put versions/<date>/ before rows or aggregate for an answer that never changes. /api/v1/datasets/<slug>/versions lists the loaded versions. The 1 newest version is loaded; versions lists them.

The API allows 60 requests in 10 seconds from one address. Above that it answers 429 for 10 seconds with a Retry-After header, a RateLimit-Policy header and a JSON body that gives the limit. Every API answer carries the same RateLimit-Policy. A client should wait the Retry-After seconds, or read the files, which have no limit. openapi.json describes this dataset's query paths for client generators and agents.

https://publicdata.au/mcp is a remote MCP server over Streamable HTTP with the same tools, defined in the same place, so a tool added to the pages is added here too. It needs no key and no account. The row tools are held to the query API's limit of 60 queries in 10 seconds from one address, and each call is two queries because it also counts the matching rows. Add it to Claude Code with claude mcp add --transport http publicdata https://publicdata.au/mcp, add the URL in Claude as a custom connector, or give it to any client that connects to remote MCP servers. Each queryable dataset is also a resource at https://publicdata.au/d/<slug>/fields.json, which lists its fields with their types, the publisher's descriptions, their ranges and the values they hold, so an agent can read a dataset's shape before it writes a query.

What changed

One version for every release the publisher has made since this site started following the dataset. The date is the day the file changed on the portal.

2026-09-11
350 rows93 fieldsutf-8-sig003377108694

versions.json · changes.json · history.tar.zst (64 KB, every version's Parquet and manifest)

Questions

How do I download Reported offences by month, Queensland as a CSV file?

Open https://publicdata.au/d/qld-offences-monthly/latest/data.csv. It redirects to the newest dated version, which is https://publicdata.au/d/qld-offences-monthly/v/2026-09-11/data.csv today. The same path serves Excel, JSON, Parquet, SQLite, DuckDB, NDJSON, Arrow. A dated URL never changes, so use it when the file must stay the same.

Can I open Reported offences by month, Queensland in Excel?

Yes. https://publicdata.au/d/qld-offences-monthly/v/2026-09-11/data.xlsx is a workbook with the 350 rows on a records sheet, the field list on a second sheet and the provenance on a third. The CSV also opens in Excel. https://publicdata.au/d/qld-offences-monthly/v/2026-09-11/data.csv.gz is the CSV at about a tenth of the size.

What years does Reported offences by month, Queensland cover?

The current version covers 1997 to 2025. Each release from QPS becomes a new dated version here, and earlier versions stay online.

How often is Reported offences by month, Queensland updated?

QPS releases it monthly. This site checks the portal every week and adds a dated version when the file changes.

Can I use Reported offences by month, Queensland commercially?

Yes. CC BY 4.0 allows commercial use, redistribution and derived works as long as the attribution is kept. The attribution string is in this page's side column and inside every file.

Is this the official source for Reported offences by month, Queensland?

No. The publisher is Queensland Police Service, and its page is https://www.data.qld.gov.au/dataset/offence-numbers-monthly-from-july-1997. This site republishes the publisher's file without changing its content. The original sits beside every version as source.csv with its SHA-256, so the two can be compared.

What this site did to the data. Cells were typed, headers were renamed and the encoding was made UTF-8. Rows were left alone. The publisher's file sits beside every version as source.csv so the change can be checked.

Attribution and citation

The licence requires the publisher's attribution. We ask that you also name publicdata.au and link to the version you used.

Queensland Police Service, Queensland Government, Queensland Offence numbers, monthly from July 1997, sourced 3 October 2026, https://www.data.qld.gov.au/dataset/offence-numbers-monthly-from-july-1997, licensed under CC BY 4.0. Serialised and versioned by National Digital at publicdata.au, https://publicdata.au/d/qld-offences-monthly/v/2026-09-11/

The attribution alone is inside every file. Harvard is the author-date form a report or a brief asks for. Paste the HTML on a web page so the links carry.

Licence record

Queensland Police Service states the licence, CC BY 4.0, on its own page, which was read and recorded here on 1 October 2026.

Every fetch reads the licence again and stops when it has changed. The fetch that made version 2026-09-11 read it from www.data.qld.gov.au on 3 October 2026.

Also published on

Hugging Faceload_dataset("National-Digital/qld-offences-monthly")
Kagglewith a starter notebook
ZenodoDOI 10.5281/zenodo.23122202

Each copy carries the same attribution and links back to this page.

For agents and tools

datapackage.jsonFrictionless data package pointing at the latest version
schema.jsonTable Schema for every field
schema.xlsxthe same field list as an Excel data dictionary
versions.jsonevery version with date, rows, fields and hash
changes.jsondiff for every consecutive pair
manifest.jsonwhere the bytes came from and when
Query APIfiltered rows and counts without a download
openapi.jsonOpenAPI 3.1 for this dataset's query paths
explore/charts and dashboards in the browser, shareable and embeddable
index.mdthis page as Markdown

This page carries a schema.org Dataset record and is listed in /.well-known/ard.json and /catalog.json.

Source

Queensland Police Service publishes this table on open-crime-data.s3-ap-southeast-2.amazonaws.com. Questions about the content go to the publisher. Questions about the files here go to corrections.

Fetched 3 October 2026. Source SHA-256 003377108694e3e1…

Improve this dataset

This page is built from register/qld-offences-monthly.yaml on GitHub. Anyone can propose a fix to it, such as a clearer description or a field the publisher renamed, as a pull request.

Report a file that differs from the publisher's · How to contribute