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Published by NSW Fair Trading under CC BY 4.0 and republished here without change to the content. NSW Fair Trading has not endorsed this site.An independent republication of open government data. No government agency has endorsed it. Read more

Rental bond refunds, New South Wales, 2021

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Publisher NSW Fair TradingUpdated no longerLicence CC BY 4.0Latest 2023-12-06Rows 329,035Fields 7

The Residential Rental Bond Refunds workbook for 2021 from NSW Fair Trading. Each row is one bond refunded in the year, with the payment date, the postcode of the rented premises, the dwelling type and number of bedrooms, the dollars paid to the agent and to the tenant, and the days the bond was held.

Also called: NSW rental bond refund data 2021, Rental bond refunds by postcode NSW 2021, Fair Trading rental bond refunds year 2021.

Part of Rental bond data, NSW Fair Trading, 10 tables the publisher releases together: Rental bond lodgements, New South Wales, 2021, Rental bond lodgements, New South Wales, 2022, Rental bond lodgements, New South Wales, 2023, Rental bond lodgements, New South Wales, 2024, Rental bond lodgements, New South Wales, 2025, Rental bond refunds, New South Wales, 2022, Rental bond refunds, New South Wales, 2023, Rental bond refunds, New South Wales, 2024, Rental bond refunds, New South Wales, 2025.

Before you use it
What is in each row?
One residential rental bond refunded by NSW Fair Trading in 2021, with the payment date, the postcode of the rented premises, the dwelling type, the number of bedrooms, the amounts paid to the agent and to the tenant, and the number of days the bond was held.
What do the dwelling type codes mean?
Fair Trading defines F as a flat or unit, H as a house, T as a terrace, townhouse or semi-detached, O as other and U as unknown. Every row in this year's file carries one of these five codes.
What does a null bedroom count mean?
Fair Trading writes U where the bedroom count was not given. It is a null value here.

Made for agents

Connect your AI agent

Any agent that connects to publicdata.au/mcp can find this dataset, read its 7 fields, count and filter across all 329,035 rows and diff its versions. Every answer names the version and carries Fair Trading's attribution. No key.

Then ask it: What does Rental bond refunds, New South Wales, 2021 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.

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
"Latest" redirects to the newest version and will change when the publisher releases again. A dated version never changes.
https://publicdata.au/d/nsw-rental-bond-refunds-2021/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/nsw-rental-bond-refunds-2021/latest/ redirects to the newest version.

https://publicdata.au/d/nsw-rental-bond-refunds-2021/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.

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.

FieldTypePublisher's headerNote
payment_datedatePayment Date
postcodestringPostcode
dwelling_typestringDwelling Type
bedroomsintegerBedrooms
payment_to_agentnumberPayment To Agent
payment_to_tenantnumberPayment To Tenant
days_bond_heldintegerDays Bond Held

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

A sample of 10 rows

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

payment_datepostcodedwelling_typebedroomspayment_to_agentpayment_to_tenantdays_bond_held
2021-12-312000F12002200346
2021-12-312000F102560244
2021-12-312000F14181582186
2021-12-312000F21653635233
2021-12-312000F202200388
2021-12-312000F2416001311
2021-12-312000F210851715362
2021-12-312000T303520402
2021-12-312000U121600760
2021-12-312000U240000688
The first row as JSON

As it appears in data.json.

GET https://publicdata.au/d/nsw-rental-bond-refunds-2021/latest/data.json
{
  "payment_date": "2021-10-08",
  "postcode": "2000",
  "dwelling_type": "F",
  "bedrooms": 0,
  "payment_to_agent": 0.0,
  "payment_to_tenant": 2340.0,
  "days_bond_held": 702
}

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.

OperatorWhat it matches
eq.valueEqual to the value.
neq.valueNot equal to the value. A blank cell does not match.
gt.valueGreater than the value.
gte.valueGreater than or equal to the value.
lt.valueLess than the value.
lte.valueLess 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.nullBlank in the source, or suppressed by the publisher.
ParameterWhat it does
selectFields to return, comma-separated. Every field when absent.
orderfield.asc or field.desc, comma-separated. The publisher's row order when absent.
limitRows per page, 1 to 10,000. 100 when absent.
offsetRows to skip. The next URL in each answer sets it for you.
groupOn aggregate, fields to group by, comma-separated.
metricOn aggregate, count, sum.field, avg.field, min.field or max.field, comma-separated. count when absent.
formatjson, 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.

versions.json · changes.json · history.tar.zst (1.7 MB, every version's Parquet and manifest)

Questions

How do I download Rental bond refunds, New South Wales as a CSV file?

Open https://publicdata.au/d/nsw-rental-bond-refunds-2021/latest/data.csv. It redirects to the newest dated version, which is https://publicdata.au/d/nsw-rental-bond-refunds-2021/v/2023-12-06/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 Rental bond refunds, New South Wales in Excel?

Yes. https://publicdata.au/d/nsw-rental-bond-refunds-2021/v/2023-12-06/data.xlsx is a workbook with the 329,035 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/nsw-rental-bond-refunds-2021/v/2023-12-06/data.csv.gz is the CSV at about a tenth of the size.

What years does Rental bond refunds, New South Wales cover?

The current version covers the years since 2021. Each release from Fair Trading becomes a new dated version here, and earlier versions stay online.

How often is Rental bond refunds, New South Wales updated?

Fair Trading no longer updates it. This site checks the portal every week and adds a dated version when the file changes.

Can I use Rental bond refunds, New South Wales 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 Rental bond refunds, New South Wales?

No. The publisher is NSW Fair Trading, and its page is https://www.nsw.gov.au/nsw-government/copyright. 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.

Rental bond data, NSW Fair Trading is 10 tables here, and each takes its version date from its own file.