Registrable life events by financial year, Victoria
liveRegistrable events by financial year from the Registry of Births, Deaths and Marriages Victoria. Each row is one kind of event and one financial year, with the number the registry registered in it. Events are counted when registered, which may differ from when they occurred. The publisher's Total row is kept.
Also called: BDM Victoria registered events by financial year, Victorian change of name registrations per year, Registered relationships Victoria per year.
Part of Births, deaths and marriages registered in Victoria, 4 tables the publisher releases together: Deaths registered per month, Victoria, Marriages registered per month, Victoria, Births, deaths and marriages registered by calendar year, Victoria.
- What does each row hold?
- The number of one kind of life event the registry registered in one financial year, from 2009/10. The kinds are births, changes of name, marriages, deaths, registered and revoked relationships, adoptions and stillbirths, and the publisher's own total of them all, kept as published.
- Have past figures changed?
- The publisher states it found and corrected an issue with the registrations first published for 2022-23. Earlier versions kept here show the figures as they were published at the time.
Made for agents
Connect your AI agent
Any agent that connects to publicdata.au/mcp can find this dataset, read its 3 fields, count and filter across all 144 rows and diff its versions. Every answer names the version and carries BDM Victoria's attribution. No key.
Then ask it: What does Registrable life events by financial year, 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=event&metric=sum.registrations&financial_year=eq.2024%2F25&event=neq.Total
Registrations by event where financial year is 2024/25 and event is not Total: 83,284 Births, 45,625 Deaths, 30,800 Marriages, 13,185 Changes of name.
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.
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-registered-events-by-financial-year/latest/ redirects to the newest version.
https://publicdata.au/d/vic-registered-events-by-financial-year/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-registered-events-by-financial-year/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-registered-events-by-financial-year")
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-registered-events-by-financial-year")
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-registered-events-by-financial-year/v/2026-07-06/data.duckdb' AS vic_registered_events_by_financial_year (READ_ONLY);
SELECT event, count(*) FROM vic_registered_events_by_financial_year.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-registered-events-by-financial-year/aggregate?group=event&metric=sum.registrations&financial_year=eq.2024%2F25&event=neq.Total");
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 |
|---|---|---|---|
| event | string | (row header 1) | |
| financial_year | string | (column header 1) | The financial year as the publisher writes it, for example 2024/25. |
| registrations | integer | (cell) |
Download this table as a data dictionary (Excel), or read it as a Frictionless Table Schema at schema.json. The key is event, financial_year.
A sample of 9 rows
Every kind of event in the newest financial year, with the publisher's total, in the publisher's order. A blank cell is shown as null.
| event | financial_year | registrations |
|---|---|---|
| Births | 2024/25 | 83284 |
| Changes of name | 2024/25 | 13185 |
| Marriages | 2024/25 | 30800 |
| Deaths | 2024/25 | 45625 |
| Registered relationships | 2024/25 | 8799 |
| Revoked relationships | 2024/25 | 1188 |
| Adoptions | 2024/25 | 53 |
| Stillbirths | 2024/25 | 412 |
| Total | 2024/25 | 183346 |
The first row as JSON
As it appears in data.json.
GET https://publicdata.au/d/vic-registered-events-by-financial-year/latest/data.json
{
"event": "Births",
"financial_year": "2024/25",
"registrations": 83284
}
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.
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.
- 2026-07-06 144 rows3 fieldsxlsxbfa5e29c12da
versions.json · changes.json · history.tar.zst (4.1 KB, every version's Parquet and manifest)
Questions
How do I download Registrable life events by financial year as a CSV file?
Open https://publicdata.au/d/vic-registered-events-by-financial-year/latest/data.csv. It redirects to the newest dated version, which is https://publicdata.au/d/vic-registered-events-by-financial-year/v/2026-07-06/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 Registrable life events by financial year in Excel?
Yes. https://publicdata.au/d/vic-registered-events-by-financial-year/v/2026-07-06/data.xlsx is a workbook with the 144 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-registered-events-by-financial-year/v/2026-07-06/data.csv.gz is the CSV at about a tenth of the size.
What years does Registrable life events by financial year cover?
The current version covers the years since 2009. Each release from BDM Victoria becomes a new dated version here, and earlier versions stay online.
How often is Registrable life events by financial year updated?
BDM Victoria releases it yearly. This site checks the portal every week and adds a dated version when the file changes.
Can I use Registrable life events by financial year 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 Registrable life events by financial year?
No. The publisher is Registry of Births, Deaths and Marriages Victoria, and its page is https://discover.data.vic.gov.au/dataset/births-deaths-and-marriages-registered-events-registered-events-by-financial-year. This site republishes the publisher's file without changing its content. The original sits beside every version as source.xlsx 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.xlsx so the change can be checked.
Births, deaths and marriages registered in Victoria is 4 tables here, and each takes its version date from its own file.