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metadata
license: mit
task_categories:
  - tabular-regression
  - time-series-forecasting
language:
  - en
tags:
  - real-estate
  - housing
  - australia
  - property-prices
  - nsw
  - property-market
  - housing-data
size_categories:
  - 1M<n<10M
configs:
  - config_name: sales
    data_files: nsw_property_sales_master.parquet
    default: true
  - config_name: enriched
    data_files: nsw_property_master_enriched.parquet
  - config_name: rental
    data_files: nsw_rental_market_master.parquet

NSW Property Dataset

The world's largest open-source dataset on New South Wales property data.

This comprehensive dataset contains over 3.6 million records spanning property sales, enriched property analytics, and rental market data for New South Wales, Australia. It covers 35 years of historical transactions from 1990 to 2024.

Dataset Overview

Config File Records Description
sales (default) nsw_property_sales_master.parquet 3,493,361 Historical property transactions (1990-2024)
enriched nsw_property_master_enriched.parquet 83,548 Properties with market analytics and demographics
rental nsw_rental_market_master.parquet 48,158 Rental bond records with pricing data

Total: 3,625,067 records

Usage

from datasets import load_dataset

# Load sales data (default configuration)
sales = load_dataset("thehooklab/nsw-property")

# Load enriched properties with analytics
enriched = load_dataset("thehooklab/nsw-property", "enriched")

# Load rental market data
rental = load_dataset("thehooklab/nsw-property", "rental")

# Example: Filter Sydney properties over $1M
sydney_premium = sales.filter(lambda x: x['locality'] == 'SYDNEY' and x['purchase_price'] > 1000000)

Data Description

Sales Data (3.49M records)

Historical property transactions across NSW from 1990 to 2024.

Column Type Description
property_id float Unique property identifier
house_number string Street number
street_name string Street name
locality string Suburb/locality name
postcode float Australian postcode
contract_date string Date of sale contract
purchase_price float Sale price in AUD
area float Property area
zone string Zoning classification
property_type string Type (HOUSE, UNIT, VACANT LAND, etc.)
sale_year int Year of sale
lat, lon float Geographic coordinates
num_bed, num_bath, num_parking float Property features
land_area float Land size in sqm
km_from_cbd float Distance from Sydney CBD
suburb_population float Population of suburb
suburb_median_income float Median income of suburb

Enriched Properties (83.5K records)

Properties enhanced with market analytics, demographic indicators, and transport accessibility scores.

Column Type Description
avg_price float Average historical price
median_price float Suburb median price
price_category string Affordable, Mid-range, Premium, Luxury
market_heat string Market activity indicator
growth_potential string Price growth forecast
rental_yield_estimate float Estimated rental yield %
days_on_market_avg float Average days to sell
auction_clearance_estimate float Auction success rate
family_friendly_score float Family suitability score
walkability_score float Pedestrian accessibility
cafe_culture_score float Local amenities score
school_rating string School quality rating
crime_index float Area crime indicator
gentrification_index float Neighborhood change indicator
nearest_station string Closest train station
distance_to_station_km float Distance to station
transport_score float Public transport accessibility

Rental Market (48.2K records)

Rental bond lodgement data with weekly rent and dwelling information.

Column Type Description
lodgement_date string Bond lodgement date
postcode float Property postcode
dwelling_type string House, Unit, Townhouse, etc.
bedrooms float Number of bedrooms
weekly_rent float Weekly rent in AUD
bond_amount float Bond amount in AUD
annual_rent float Calculated annual rent

Use Cases

  • Property Price Prediction: Train ML models to predict property values
  • Market Analysis: Analyze price trends across suburbs and time periods
  • Investment Research: Identify high-growth areas and rental yields
  • Urban Planning: Study development patterns and demographic shifts
  • Academic Research: Housing affordability, market dynamics studies

Data Quality

  • All numeric columns validated and cleaned
  • String columns properly typed to avoid parsing errors
  • Coordinates available for properties with geolocation data
  • Data sourced from official NSW government records and verified sources

Citation

If you use this dataset in your research or projects, please cite:

@dataset{nsw_property_2026,
  title={NSW Property Dataset: The World's Largest Open-Source NSW Property Data},
  author={Fedor Kriuk},
  year={2026},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/thehooklab/nsw-property}
}

License

MIT License - Free to use for commercial and non-commercial purposes.

Contributing

Found an issue or have suggestions? Open an issue on the dataset repository.