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India Housing Market Snapshot
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About
This dataset provides a detailed analysis of residential property prices in urban India, offering key trends and insights into the market. It encompasses a rich array of property features, designed for deep real estate market analysis and advanced predictive modelling. The data facilitates an understanding of the diverse factors that influence house prices across various regions within India.
Columns
- id: A unique identifier assigned to each property listing.
- Date: The specific date when the property was listed or successfully sold.
- number of bedrooms: Indicates the total count of bedrooms present within the house.
- number of bathrooms: Specifies the total count of bathrooms available in the house.
- living area: Represents the total habitable area of the property, measured in square feet.
- lot area: Denotes the total land area associated with the property, expressed in square feet.
- number of floors: Details the total number of levels or floors in the house.
- waterfront present: A binary indicator (1 for yes, 0 for no) signifying if the property boasts a waterfront view.
- number of views: Records the total number of times the property listing was viewed.
- condition of the house: An assessment of the house's overall condition, typically on a scale (e.g., 1 to 5).
- grade of the house: The assessed grade of the house, ranging from 4 to 13, reflecting its quality.
- Area of the house(excluding basement): The area of the main house structure, excluding any basement space.
- Area of the basement: The total area of the property's basement, if present.
- Built Year: The year in which the property was originally constructed.
- Renovation Year: The year in which the property underwent its most recent renovation. A value of 0 typically indicates no recorded renovation.
- Postal Code: The postal code corresponding to the property's location.
- Lattitude: The geographic latitude coordinate of the property.
- Longitude: The geographic longitude coordinate of the property.
- living_area_renov: The living area of the property after any renovation, in square feet.
- lot_area_renov: The lot area of the property after any renovation, in square feet.
- Number of schools nearby: The count of schools located in the immediate vicinity of the property.
- Distance from the airport: The measured distance from the property to the nearest airport.
- Price: The sale or listing price of the property.
Distribution
The dataset is provided as a CSV file, named "House Price India.csv", with a file size of 1.52 MB. It contains 23 columns and comprises approximately 14,600 individual property records. The dataset is static and does not have an expected update frequency, meaning it is not planned for future updates.
Usage
This dataset is an excellent resource for a variety of applications, including:
- Real estate market analysis: Gaining insights into pricing trends, property valuations, and market dynamics in urban India.
- Predictive modelling: Developing models to forecast property prices based on various features.
- Urban planning research: Studying the impact of infrastructure (like schools and airports) and geographic factors on housing values.
- Economic research: Analysing regional economic indicators and their correlation with residential property markets.
Coverage
The data focuses on residential properties within urban India. The time range for property listings and sales, as well as construction and renovation years, spans from approximately 1900 to 2015. While specific demographic details are not provided, the data includes geographical coordinates and postal codes for location-based analysis.
License
CC0: Public Domain
Who Can Use It
- Real estate analysts: To identify market trends, perform valuations, and understand factors affecting property prices.
- Data scientists: For building and refining machine learning models to predict house prices.
- Urban planners and policy makers: To inform housing policies and development strategies.
- Investors and property developers: To make informed decisions on acquisitions, sales, and new developments.
Dataset Name Suggestions
- Urban India House Prices
- Indian Residential Property Data
- India Housing Market Snapshot
- Real Estate Prices in Urban India
- Indian Property Value Predictor Dataset
Attributes
Original Data Source: India Housing Market Snapshot
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