2 datasets found
  1. House Prices in Malaysia (2025)

    • kaggle.com
    zip
    Updated Jan 3, 2025
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    Jien Weng (2025). House Prices in Malaysia (2025) [Dataset]. https://www.kaggle.com/datasets/lyhatt/house-prices-in-malaysia-2025
    Explore at:
    zip(39697 bytes)Available download formats
    Dataset updated
    Jan 3, 2025
    Authors
    Jien Weng
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Malaysia
    Description

    This dataset contains 2,000 entries of house price data from all states in Malaysia, providing a comprehensive overview of the country’s real estate market for 2025. Sourced from Brickz, a trusted platform for property transaction insights, it includes detailed information such as property location, tenure, type, median prices, and transaction counts. This dataset is ideal for real estate market analysis, predictive modeling, and exploring trends across Malaysia’s diverse property market.

    https://encrypted-tbn1.gstatic.com/licensed-image?q=tbn:ANd9GcR8ttDRWTx7dIxuUegBTsggS4a6tQrnNA6DEW_HJu2DphQNsverV0PYsSkdbSdqm4qRaRuBOh4Txbv11yXMxIKWqh-_WAkeTuQI8Diu-Q" alt="Kuala Lumpur, Malaysia">

    Data Columns (Total 8 Columns):

    1. Township: The specific township where the property is located (e.g., Cheras, Subang Jaya).
    2. Area: The locality or broader area encompassing the township (e.g., Klang Valley, Penang Island).
    3. State: The Malaysian state where the property is situated (e.g., Selangor, Johor, Penang).
    4. Tenure: The property ownership type (e.g., Freehold, Leasehold).
    5. Type: The category of property (e.g., Terrace, Condominium, Semi-Detached).
    6. Median_Price: The median price (in MYR) for properties in the specified township or area.
    7. Median_PSF: The median price per square foot (in MYR) for properties.
    8. Transactions: The number of recorded property transactions.

    Future Plans:

    • Expanded Coverage: This dataset will be regularly updated with additional property data to make it even more versatile.
    • Enhanced Features: Future updates may include rental prices, amenities, or property-specific details to offer deeper insights into Malaysia’s housing market.
  2. h

    housing-prices-malaysia-2025

    • huggingface.co
    Updated Jan 31, 2025
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    Lai JIen Weng (2025). housing-prices-malaysia-2025 [Dataset]. https://huggingface.co/datasets/jienweng/housing-prices-malaysia-2025
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 31, 2025
    Authors
    Lai JIen Weng
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    This dataset contains 2,000 entries of house price data from all states in Malaysia, providing a comprehensive overview of the country’s real estate market for 2025. Sourced from Brickz, a trusted platform for property transaction insights, it includes detailed information such as property location, tenure, type, median prices, and transaction counts. This dataset is ideal for real estate market analysis, predictive modeling, and exploring trends across Malaysia’s diverse property market.… See the full description on the dataset page: https://huggingface.co/datasets/jienweng/housing-prices-malaysia-2025.

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Share
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Email
Click to copy link
Link copied
Close
Cite
Jien Weng (2025). House Prices in Malaysia (2025) [Dataset]. https://www.kaggle.com/datasets/lyhatt/house-prices-in-malaysia-2025
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House Prices in Malaysia (2025)

2000 Property Listings Across Malaysia with Detailed Attributes and Pricing

Explore at:
zip(39697 bytes)Available download formats
Dataset updated
Jan 3, 2025
Authors
Jien Weng
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Area covered
Malaysia
Description

This dataset contains 2,000 entries of house price data from all states in Malaysia, providing a comprehensive overview of the country’s real estate market for 2025. Sourced from Brickz, a trusted platform for property transaction insights, it includes detailed information such as property location, tenure, type, median prices, and transaction counts. This dataset is ideal for real estate market analysis, predictive modeling, and exploring trends across Malaysia’s diverse property market.

https://encrypted-tbn1.gstatic.com/licensed-image?q=tbn:ANd9GcR8ttDRWTx7dIxuUegBTsggS4a6tQrnNA6DEW_HJu2DphQNsverV0PYsSkdbSdqm4qRaRuBOh4Txbv11yXMxIKWqh-_WAkeTuQI8Diu-Q" alt="Kuala Lumpur, Malaysia">

Data Columns (Total 8 Columns):

  1. Township: The specific township where the property is located (e.g., Cheras, Subang Jaya).
  2. Area: The locality or broader area encompassing the township (e.g., Klang Valley, Penang Island).
  3. State: The Malaysian state where the property is situated (e.g., Selangor, Johor, Penang).
  4. Tenure: The property ownership type (e.g., Freehold, Leasehold).
  5. Type: The category of property (e.g., Terrace, Condominium, Semi-Detached).
  6. Median_Price: The median price (in MYR) for properties in the specified township or area.
  7. Median_PSF: The median price per square foot (in MYR) for properties.
  8. Transactions: The number of recorded property transactions.

Future Plans:

  • Expanded Coverage: This dataset will be regularly updated with additional property data to make it even more versatile.
  • Enhanced Features: Future updates may include rental prices, amenities, or property-specific details to offer deeper insights into Malaysia’s housing market.
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