Update README.md

README.md

@@ -11,6 +11,8 @@ tags:
   - australia
   - property-prices
   - nsw
+  - property-market
+  - housing-data
 size_categories:
   - 1M<n<10M
 configs:
@@ -25,51 +27,136 @@ configs:
 
 # NSW Property Dataset
 
-Comprehensive property market data for New South Wales, Australia.
+**The world's largest open-source dataset on New South Wales property data.**
 
-## Dataset Configurations
+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.
 
-| Config | File | Rows | Description |
-|--------|------|------|-------------|
-| `sales` (default) | `nsw_property_sales_master.parquet` | 3.49M | Historical property transactions 1990-2024 |
-| `enriched` | `nsw_property_master_enriched.parquet` | 83.5K | Properties with analytics, demographics, transport |
-| `rental` | `nsw_rental_market_master.parquet` | 48.2K | Rental bond records with pricing |
+## 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
 
 ```python
 from datasets import load_dataset
 
-# Load sales data (default)
+# Load sales data (default configuration)
 sales = load_dataset("thehooklab/nsw-property")
 
-# Load enriched properties
+# Load enriched properties with analytics
 enriched = load_dataset("thehooklab/nsw-property", "enriched")
 
-# Load rental data
+# 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)
 ```
 
-## Key Features
+## 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)
 
-**Sales Data:**
-- Property ID, address, locality, postcode
-- Contract date and purchase price
-- Property type, zone, land area
-- Coordinates (lat/lon for some records)
+Rental bond lodgement data with weekly rent and dwelling information.
 
-**Enriched Properties:**
-- Market analytics (median prices, growth potential)
-- Rental yield estimates
-- Transport accessibility (nearest station, distance)
-- Demographics (walkability, family-friendly scores)
-- School ratings and crime indices
+| 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 |
 
-**Rental Data:**
-- Lodgement dates and weekly rent
-- Dwelling types and bedrooms
-- Bond amounts
+## 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:
+
+```bibtex
+@dataset{nsw_property_2026,
+  title={NSW Property Dataset: The World's Largest Open-Source NSW Property Data},
+  author={TheHookLab},
+  year={2026},
+  publisher={HuggingFace},
+  url={https://huggingface.co/datasets/thehooklab/nsw-property}
+}
+```
 
 ## License
 
-MIT 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.
+