Explore a detailed apartment rental dataset perfect for machine learning tasks like clustering, classification, and regression.

This dataset comprises detailed information on apartment rentals, ideal for various machine learning tasks including clustering, classification, and regression. It features a comprehensive set of attributes that capture essential aspects of rental listings, such as:

Identifiers & Location: Includes unique identifiers (id), geographic details (address, cityname, state, latitude, longitude), and the source of the classified listing. Property Details: Provides information on the apartment's category, title, body, amenities, number of bathrooms, bedrooms, and square_feet (size of the apartment). Pricing Information: Contains multiple features related to pricing, including price (rental price), price_display (displayed price), price_type (price in USD), and fee. Additional Features: Indicates whether the apartment has a photo (has_photo), whether pets are allowed (pets_allowed), and other relevant details such as currency and time of listing creation. The dataset is well-cleaned, ensuring that critical columns like price and square_feet are never empty. This makes it a robust resource for developing predictive models and performing in-depth analyses on rental trends and property characteristics.