School locations, Victoria
liveThe Department of Education's School Locations list for 2025, one row per school with its sector, school number, type, status, street and postal addresses, phone number, departmental region and area, council area and longitude and latitude. Government and non-government schools are both included. The department publishes a new list each year.
Also called: Victorian school locations, Victorian schools list, School Locations 2025, Victorian government and non-government schools.
Part of Victorian schools and school zones, 3 tables the publisher releases together: Government primary school zones for 2027, Victoria, Government secondary school zones for Year 7 in 2027, Victoria.
- What does each row hold?
- One school registered in Victoria, government, Catholic or independent, with its school number, name, type, street and postal address, phone number, the department's region and area, the council area and the coordinates of the school. The publisher collects it as part of the registration of schools, as at the February census.
- Which schools are included?
- Primary, secondary, combined primary and secondary, specialist and English language schools of every sector. A school with more than one campus is listed once, at its administration campus, and the region and area follow that campus.
- What do the status and entity type codes mean?
- The status is O for an open school and C for a closed one, as published. The entity type is 1 for a government school and 2 for a non-government school, and a school number is unique within its entity type.

Made for agents
Connect your AI agent
Any agent that connects to publicdata.au/mcp can find this dataset, read its 24 fields, count and filter across all 2,301 rows and diff its versions. Every answer names the version and carries Education's attribution. No key.
Then ask it: What does School locations, Victoria 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.
Settings, then Connectors, then Add custom connector, and paste https://publicdata.au/mcp.
On the web and in the desktop app.
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.
A dashboard over every row. Click to filter, add panels, share a link or embed a frame.
Query APIFilter and count from a URLaggregate?group=school_type&metric=count&education_sector=eq.Government
Schools by school type where sector is Government: 1,147 Primary, 258 Secondary, 85 Special, 80 Pri/Sec.
Download it as Excel, CSV, JSON and 9 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.
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/vic-school-locations/latest/ redirects to the newest version.
https://publicdata.au/d/vic-school-locations/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/vic-school-locations/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("vic-school-locations")
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("vic-school-locations")
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/vic-school-locations/v/2025-08-29/data.duckdb' AS vic_school_locations (READ_ONLY);
SELECT education_sector, count(*) FROM vic_school_locations.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/vic-school-locations/aggregate?group=school_type&metric=count&education_sector=eq.Government");
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.
| Field | Type | Publisher's header | Note |
|---|---|---|---|
| education_sector | string | Education_Sector | Government, Catholic or Independent. |
| entity_type | integer | Entity_Type | 1 for a government school, 2 for a non-government school. |
| school_no | integer | School_No | |
| school_name | string | School_Name | |
| school_type | string | School_Type | Primary, Secondary, Pri/Sec, Special or Language. |
| school_status | string | School_Status | O for open, C for closed. |
| address_line_1 | string | Address_Line_1 | |
| address_line_2 | string | Address_Line_2 | |
| address_town | string | Address_Town | |
| address_state | string | Address_State | |
| address_postcode | string | Address_Postcode | |
| postal_address_line_1 | string | Postal_Address_Line_1 | |
| postal_address_line_2 | string | Postal_Address_Line_2 | |
| postal_town | string | Postal_Town | |
| postal_state | string | Postal_State | |
| postal_postcode | string | Postal_Postcode | |
| full_phone_no | string | Full_Phone_No | |
| region | string | Region | |
| area | string | Area | |
| lga_id | integer | LGA_ID | The council area's code in the department's list. |
| lga_name | string | LGA_Name | |
| lga_type | string | LGA_TYPE | Metro, Non Metro or Unknown. |
| x | number | X | |
| y | number | Y |
Download this table as a data dictionary (Excel), or read it as a Frictionless Table Schema at schema.json. The key is entity_type, school_no.
A sample of 10 rows
From the latest version, each sector in turn, then in the publisher's order, with every field. A blank cell is shown as null.
| education_sector | entity_type | school_no | school_name | school_type | school_status | address_line_1 | address_line_2 | address_town | address_state | address_postcode | postal_address_line_1 | postal_address_line_2 | postal_town | postal_state | postal_postcode | full_phone_no | region | area | lga_id | lga_name | lga_type | x | y |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Catholic | 2 | 20 | Parade College | Secondary | O | 1436 Plenty Road | null | BUNDOORA | VIC | 3083 | 1436 Plenty Road | null | BUNDOORA | VIC | 3083 | 03 9468 3300 | NORTH-WESTERN VICTORIA | North Eastern Melbourne | 66 | Banyule (C) | Metro | 145.066978 | -37.690178 |
| Government | 1 | 1 | Alberton Primary School | Primary | O | 21 Thomson Street | null | Alberton | VIC | 3971 | 21 Thomson Street | null | ALBERTON | VIC | 3971 | 03 5183 2412 | SOUTH-EASTERN VICTORIA | Outer Gippsland | 681 | Wellington (S) | Non Metro | 146.666601 | -38.617713 |
| Independent | 2 | 1 | Wesley College | Pri/Sec | O | 577 St Kilda Road | null | MELBOURNE | VIC | 3004 | 577 St Kilda Road | null | MELBOURNE | VIC | 3004 | 03 8102 6100 | SOUTH-WESTERN VICTORIA | Western Melbourne | 460 | Melbourne (C) | Metro | 144.982144 | -37.84883 |
| Catholic | 2 | 25 | Simonds Catholic College | Secondary | O | 273 Victoria Street | null | WEST MELBOURNE | VIC | 3003 | 273 Victoria Street | null | WEST MELBOURNE | VIC | 3003 | 03 9321 9200 | SOUTH-WESTERN VICTORIA | Western Melbourne | 460 | Melbourne (C) | Metro | 144.952883 | -37.805971 |
| Government | 1 | 3 | Allansford and District Primary School | Primary | O | Frank Street | null | Allansford | VIC | 3277 | Frank Street | null | ALLANSFORD | VIC | 3277 | 03 5565 1382 | SOUTH-WESTERN VICTORIA | Wimmera South West | 673 | Warrnambool (C) | Non Metro | 142.590393 | -38.386281 |
| Independent | 2 | 5 | Korowa Anglican Girls' School | Pri/Sec | O | 10 - 16 Ranfurlie Crescent | null | GLEN IRIS | VIC | 3146 | 10 - 16 Ranfurlie Crescent | null | GLEN IRIS | VIC | 3146 | 03 9811 0200 | SOUTH-EASTERN VICTORIA | Bayside Peninsula | 635 | Stonnington (C) | Metro | 145.054637 | -37.861454 |
| Catholic | 2 | 26 | St Mary’s College Melbourne | Secondary | O | 11 Westbury Street | null | ST KILDA EAST | VIC | 3183 | PO Box 258 | null | ST KILDA | VIC | 3182 | 03 9529 6611 | SOUTH-EASTERN VICTORIA | Bayside Peninsula | 590 | Port Phillip (C) | Metro | 144.997001 | -37.859365 |
| Government | 1 | 4 | Avoca Primary School | Primary | O | 118 Barnett Street | null | Avoca | VIC | 3467 | P O Box 12 | null | AVOCA | VIC | 3467 | 03 5465 3176 | SOUTH-WESTERN VICTORIA | Central Highlands | 599 | Pyrenees (S) | Non Metro | 143.475649 | -37.084502 |
| Independent | 2 | 83 | Ruyton Girls' School | Pri/Sec | O | 12 Selbourne Road | null | KEW | VIC | 3101 | 12 Selbourne Road | null | KEW | VIC | 3101 | 03 9819 2422 | NORTH-EASTERN VICTORIA | Inner Eastern Melbourne | 111 | Boroondara (C) | Metro | 145.039181 | -37.811111 |
| Catholic | 2 | 28 | St Patrick's College Ballarat | Secondary | O | 1431 Sturt Street | null | BALLARAT | VIC | 3350 | Locked Bag 31 | null | BALLARAT | VIC | 3350 | 03 5331 1688 | SOUTH-WESTERN VICTORIA | Central Highlands | 57 | Ballarat (C) | Non Metro | 143.831558 | -37.559711 |
The first row as JSON
As it appears in data.json.
GET https://publicdata.au/d/vic-school-locations/latest/data.json
{
"education_sector": "Catholic",
"entity_type": 2,
"school_no": 20,
"school_name": "Parade College",
"school_type": "Secondary",
"school_status": "O",
"address_line_1": "1436 Plenty Road",
"address_line_2": null,
"address_town": "BUNDOORA",
"address_state": "VIC",
"address_postcode": "3083",
"postal_address_line_1": "1436 Plenty Road",
"postal_address_line_2": null,
"postal_town": "BUNDOORA",
"postal_state": "VIC",
"postal_postcode": "3083",
"full_phone_no": "03 9468 3300",
"region": "NORTH-WESTERN VICTORIA",
"area": "North Eastern Melbourne",
"lga_id": 66,
"lga_name": "Banyule (C)",
"lga_type": "Metro",
"x": 145.066978,
"y": -37.690178
}
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.
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.
Smaller files
The same rows split by a field, one JSON file each with a GeoJSON beside it. Each file carries the same provenance header.
By education_sector (3 files)
by/education_sector/index.json lists every file with its row count.
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.
- 2025-08-29 2,301 rows24 fieldsutf-8-sigd2703eaa7569
versions.json · changes.json · history.tar.zst (167 KB, every version's Parquet and manifest)
Questions
How do I download School locations as a CSV file?
Open https://publicdata.au/d/vic-school-locations/latest/data.csv. It redirects to the newest dated version, which is https://publicdata.au/d/vic-school-locations/v/2025-08-29/data.csv today. The same path serves Excel, JSON, GeoJSON, Parquet, SQLite, DuckDB, GeoPackage, GeoParquet, NDJSON, Arrow. A dated URL never changes, so use it when the file must stay the same.
Can I open School locations in Excel?
Yes. https://publicdata.au/d/vic-school-locations/v/2025-08-29/data.xlsx is a workbook with the 2,301 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/vic-school-locations/v/2025-08-29/data.csv.gz is the CSV at about a tenth of the size.
What years does School locations cover?
The current version covers the years since 2025. Each release from Education becomes a new dated version here, and earlier versions stay online.
How often is School locations updated?
Education releases it yearly. This site checks the portal every week and adds a dated version when the file changes.
Can I use School locations 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 School locations?
No. The publisher is Department of Education, and its page is https://discover.data.vic.gov.au/dataset/school-locations-2025. 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.
How do I get only the rows for one education sector?
Every version has one JSON file per value of education_sector, 3 files in the current version, listed with row counts at https://publicdata.au/d/vic-school-locations/v/2025-08-29/by/education_sector/index.json. For example https://publicdata.au/d/vic-school-locations/v/2025-08-29/by/education_sector/government.json holds the 1,575 rows where education_sector is Government. A GeoJSON file sits beside each one.
What coordinate system does School locations use?
The publisher names no datum. The coordinates are decimal degrees, read as WGS84 (EPSG:4326) and published as given. The GeoJSON file uses the same coordinates, which is what GeoJSON expects.
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.
Victorian schools and school zones is 3 tables here, and each takes its version date from its own file.