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NL House Price Prediction Dataset
Comodities & Real Estate
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About
This collection of structured data offers detailed information on the residential housing market in the Netherlands. It was initially assembled to support a personal initiative focused on the prediction of house prices. The underlying data, covering information on over 5,000 houses, was sourced by retrieving listings from Funda, which is the largest real estate website operating within the Netherlands. The product contains key property characteristics, including basic location details, the asking price, the building's structural features (such as the number of rooms and bathrooms), the construction year, and the type of building.
Columns
- Address: The specific street address where the property is located.
- City: The city in which the property is situated (e.g., Eindhoven or Apeldoorn).
- Price: The financial value (ask price) set for the house by the seller.
- Lot size (m2): The measured area of the full lot in square meters.
- Living space size (m2): The measured internal size of the house in square meters.
- Build year: The chronological year when the house was constructed.
- Build type: Describes whether the building is an existing construction (Bestaande bouw) or a newly built property (Nieuwbouw).
- House type: A combined descriptor detailing the dwelling type (e.g., terraced house, villa) and its specific placement (e.g., detached).
- Roof: Defines the material and type of roof structure, such as a hipped roof covered with tiles (Zadeldak bedekt met pannen).
- Rooms: The total count of rooms, specifying the number of bedrooms included (e.g., 5 rooms (4 bedrooms)).
- Toilet: Details the quantity of bathrooms and separate toilets available (e.g., 1 bathroom and 1 separate toilet).
- Floors: The number of residential levels present, including basements or lofts (e.g., 3 residential levels).
- Energy label: The efficiency rating assigned to the house, ranging from A+++ (most efficient) to F (least efficient).
- Position: Explains the property's setting within the street or neighbourhood (e.g., on a quiet road and in a residential area).
- Garden: The types of external garden spaces attached to the property (e.g., back garden and front garden).
- Estimated neighbourhood price per m2: The estimated price per square meter for other properties located in the same neighbourhood.
Distribution
The data is delivered in a standard CSV file format, typically named
raw_data.csv. It contains 16 distinct columns and 5,555 individual records or rows. Updates to the underlying source information are expected to occur annually.Usage
This resource is ideally suited for developing predictive models, particularly those using machine learning techniques, aimed at forecasting property values in the Dutch market. It is highly beneficial for real estate analysts assessing the influence of specific features or location attributes on price.
Coverage
The geographic scope of the dataset is restricted exclusively to the Netherlands. The dataset focuses solely on residential properties. While specific time boundaries are not noted, the information reflects current and recently listed properties.
License
CC BY-NC-SA 4.0
Who Can Use It
Intended users include data scientists requiring structured input for machine learning, financial analysts evaluating investment opportunities or mortgage risk in the housing sector, and researchers studying urban economics and property valuation in Europe.
Dataset Name Suggestions
- Netherlands Residential Property Data
- Dutch Housing Market Descriptors
- NL House Price Prediction Dataset
- Funda Real Estate Metrics
Attributes
Original Data Source: NL House Price Prediction Dataset
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