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Apartment Listing Data USA
Data Science and Analytics
Tags and Keywords
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Free
About
This collection features classified advertisements for apartments available for rent within the USA. It provides the core textual content, location details, pricing, and specific amenity information for each listing. This resource is highly valuable for understanding current rental market trends, analysing geographical pricing differences, and developing automated tools for housing market research.
Columns
The collection includes 22 distinct fields detailing aspects of the rental property and listing:
- id: A unique identifying value for each apartment entry.
- category: The general classification of the rental (e.g., number of bedrooms).
- title: The primary title text used in the apartment advertisement.
- body: The main descriptive text for the apartment.
- amenities: Details specific features available, such as AC, pool, gym, internet access, cable, and refrigerator.
- bathrooms: The quantity of bathrooms in the unit.
- bedrooms: The quantity of bedrooms in the unit.
- currency: The currency denomination of the rental price.
- fee: Any additional fees that may be charged by the dealer.
- has_photo: Indicates whether a photograph of the apartment was included in the listing.
- pets_allowed: Specifies which types of pets (e.g., dogs, cats) are permitted.
- price: The numerical value of the rental price.
- price_display: The rental price formatted for reader viewing.
- price_type: Indicates the payment type based on the period (e.g., USD).
- square_feet: The area space of the apartment unit.
- address, cityname, state: Specific geographical location details.
- latitude, longitude: Coordinate data corresponding to the apartment's location.
- source: The originating platform of the classified advertisement.
- time: The date and time when the classified listing was created.
Distribution
The collection structure typically involves a data file, often delivered in a CSV format. The file, named
apartments_for_rent_classified_100K.csv, is approximately 102.22 MB in size. It contains either 10,000 or 100,000 rental entries, divided across 22 columns. Although price and size fields are generally present, a significant amount of data is missing across various columns, particularly location and time data, which can have missing rates up to 73%.Usage
This collection is ideally suited for several machine learning and data science applications:
- Developing Regression models to predict rental price or square footage based on listing attributes.
- Implementing Classification models based on the category of the classified rental.
- Applying Clustering techniques to discover new features or segmentation within the rental market.
- Creating Recommendation Systems for suggesting apartments to users.
- Conducting Geo Data Analysis to map pricing and availability geographically.
Coverage
The data focuses geographically on classified apartment rentals located within the United States. While the time field tracks the creation date of the classified ad, the specific span of time covered is not detailed. The scope includes apartment listings sourced from various rental listing platforms.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
Intended users include data scientists and machine learning engineers looking for real-world text and tabular data to train predictive models for the housing sector. Real estate analysts can use the data for market research, understanding regional pricing dynamics, and performing spatial analysis. The collection is also suitable for students and beginners entering data science, as it is tagged as an entry-level resource.
Dataset Name Suggestions
- US Rental Classifieds 100K
- Apartment Listing Data USA
- American Rental Adverts
- Property Rent Classifieds
Attributes
Original Data Source: Apartment Listing Data USA
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