Data Description

This dataset contains housing data for a real estate challenge. The goal is to predict the price of a house based on its features.

Files

train.csv - The training set, containing all features and the target variable, price.

test.csv - The test set, containing all features except the target variable. Your task is to predict the price for these properties.

sample_submission.csv - A sample submission file in the correct format. It must contain an id and your predicted price.

Columns

id - (Generated) A unique identifier for each property.

price - (Target Variable) The sale price of the house in raw currency (e..g, 13300000).

area - The total area of the property in square feet.

bedrooms - The number of bedrooms in the house.

bathrooms - The number of bathrooms in the house.

stories - The number of stories (floors) in the house.

mainroad - (Binary) 1 if the house is connected to the main road, 0 otherwise.

guestroom - (Binary) 1 if the house has a guest room, 0 otherwise.

basement - (Binary) 1 if the house has a basement, 0 otherwise.

hotwaterheating - (Binary) 1 if the house has hot water heating, 0 otherwise.

airconditioning - (Binary) 1 if the house has air conditioning, 0 otherwise.

parking - The number of parking spots available.

prefarea - (Binary) 1 if the house is located in a preferred area, 0 otherwise.

furnishingstatus - (Categorical) The furnishing status of the house.