Dark Mode
New Delhi Rental Market Features
Product Reviews & Feedback
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
Data featuring rental listings across the Delhi/NCR region, originally compiled for a rental price prediction project. It includes over 17,900 records detailing various property types such as Apartments, Independent floors, Independent houses, and Villas. This collection is useful for analysing areas of affluence and housing market trends in the region.
Columns
The dataset contains quantitative, categorical, and coordinate features:
- size_sq_ft: The size of the property measured in Square Feet.
- propertyType: The type of property being rented, such as 'Independent Floor' or 'Apartment'.
- bedrooms: The number of bedrooms in the listing.
- latitude & longitude: Geographical coordinates of the property location.
- localityName: Specific locality or street name where the property is situated.
- suburbName: The broader region within New Delhi (e.g., Delhi South).
- cityName: The city, consistently identified as Delhi.
- price: The monthly asking rent for the property.
- companyName: Identifies the associated Rental Agency or individual.
- closest_mtero_station_km: Geodesic distance (in kilometres) to the nearest metro station.
- AP_dist_km: Geodesic distance to the Indira Gandhi International Airport.
- Aiims_dist_km: Geodesic distance to the All India Institute of Medical Science (major hospital).
- NDRLW_dist_km: Geodesic distance to the New Delhi Railway Station.
Distribution
The dataset, titled June_8_data_metro_closest_stations.csv, is structured with 15 fields (columns). The file size is 3.22 MB, containing approximately 17,900 valid records. The data is usually available in CSV format.
Usage
This data is ideal for various analytical tasks, particularly:
- Developing machine learning models for rental price forecasting and regression tasks.
- Performing geospatial analysis to study the impact of proximity to landmarks (metro, airport, railway station) on housing prices.
- Analysing housing trends, property type distribution, and identifying pockets of economic significance (areas of affluence).
Coverage
The data is strictly focused on rental listings within the New Delhi/NCR area, including suburbs like Delhi South and Delhi Central. The collection represents a static snapshot; the expected update frequency is 'Never'.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Machine Learning Engineers: For building predictive models concerning real estate valuation and regression.
- Urban Researchers and Planners: For detailed geospatial studies related to urban density and infrastructure proximity.
- Real Estate Professionals: To gain insights into pricing strategies and market variations across different localities in the NCR.
Dataset Name Suggestions
- New Delhi Rental Market Features
- NCR Real Estate Price Drivers
- Geospatial Housing Listings (Delhi)
- Delhi Rental Prediction Attributes
Attributes
Original Data Source: New Delhi Rental Market Features
QUALITYLoading...