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Real Estate Market Prices
Data Science and Analytics
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About
This dataset offers detailed features of residential properties alongside their corresponding prices. It serves as a valuable resource for exploring and analysing the various factors that influence housing prices. Furthermore, it is well-suited for developing and training predictive models to estimate property valuations based on their unique characteristics.
Columns
- price: The monetary value of the property. Data ranges from £1.75 million to £13.3 million, with an average of £4.77 million.
- area: The total square footage of the property. Measurements span from 1,650 to 16,200 square feet, averaging 5,150 square feet.
- bedrooms: The total count of bedrooms within the property. This varies from 1 to 6 bedrooms, with an average of 2.97.
- bathrooms: The total count of bathrooms in the property. Typically, properties have 1 to 4 bathrooms, with an average of 1.29.
- stories: The number of floors in the property. Properties have between 1 and 4 stories, averaging 1.81 stories.
- mainroad: A binary indicator (yes/no) specifying if the property is located on a main road. 86% of properties are on a main road.
- guestroom: A binary indicator (yes/no) for the presence of a guest room. 18% of properties include a guest room.
- basement: A binary indicator (yes/no) for the presence of a basement. 35% of properties have a basement.
- hotwaterheating: A binary indicator (yes/no) for hot water heating availability. 5% of properties are equipped with hot water heating.
- airconditioning: A binary indicator (yes/no) for air conditioning availability. 32% of properties have air conditioning.
- parking: The number of available parking spaces. This ranges from 0 to 3 spaces, with an average of 0.69.
- prefarea: A binary indicator (yes/no) signifying if the property is located in a preferred area. 23% of properties are in a preferred area.
- furnishingstatus: Describes the property's furnishing status, such as furnished, semi-furnished, or unfurnished. The most common status is semi-furnished (42%), followed by unfurnished (33%).
Distribution
This dataset is provided in a CSV format (
Housing_Price_Data.csv) and has a size of 29.98 kB. It contains 13 columns and consists of 545 records of residential property data. The data is structured in a tabular format.Usage
This dataset is ideal for:
- Exploratory data analysis to uncover relationships and trends between various housing features and their prices.
- Building machine learning models aimed at predicting housing prices based on a property's given attributes.
- Market research to understand property valuation drivers.
Coverage
The dataset focuses on residential properties, providing detailed attributes. However, specific geographic locations, time ranges, or demographic scopes are not detailed within the available information.
License
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Who Can Use It
- Data analysts interested in understanding real estate market dynamics and pricing factors.
- Machine learning engineers developing and testing predictive models for property valuations.
- Real estate professionals seeking data-driven insights for property assessment and market trends.
- Researchers studying housing economics and urban development.
Dataset Name Suggestions
- Housing Price Data
- Residential Property Valuations
- Real Estate Market Prices
- Property Feature Analysis
- UK Property Valuation Dataset
Attributes
Original Data Source: Real Estate Market Prices
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