Name: India House Data
Creator: Kaggle
License: http://opendatacommons.org/licenses/dbcl/1.0/

About this Dataset

India House Data

Welcome to the House Price Prediction Challenge, you will test your regression skills by designing an algorithm to accurately predict the house prices in India. Accurately predicting house prices can be a daunting task. The buyers are just not concerned about the size(square feet) of the house and there are various other factors that play a key role to decide the price of a house/property.

Tables

Bangalore House Data

@kaggle.saipavansaketh_pune_house_data.bangalore_house_data

168.7 kB
13,320 rows
9 columns

CREATE TABLE bangalore_house_data (
  "area_type" VARCHAR,
  "availability" VARCHAR,
  "location" VARCHAR,
  "size" VARCHAR,
  "society" VARCHAR,
  "total_sqft" VARCHAR,
  "bath" DOUBLE,
  "balcony" DOUBLE,
  "price" DOUBLE
);

Delhi House Data

@kaggle.saipavansaketh_pune_house_data.delhi_house_data

37.89 kB
1,259 rows
11 columns

CREATE TABLE delhi_house_data (
  "area" DOUBLE,
  "bhk" BIGINT,
  "bathroom" DOUBLE,
  "furnishing" VARCHAR,
  "locality" VARCHAR,
  "parking" DOUBLE,
  "price" BIGINT,
  "status" VARCHAR,
  "transaction" VARCHAR,
  "type" VARCHAR,
  "per_sqft" DOUBLE
);

Pune House Data

@kaggle.saipavansaketh_pune_house_data.pune_house_data

137.7 kB
13,320 rows
9 columns

CREATE TABLE pune_house_data (
  "area_type" VARCHAR,
  "availability" VARCHAR,
  "size" VARCHAR,
  "society" VARCHAR,
  "total_sqft" VARCHAR,
  "bath" DOUBLE,
  "balcony" DOUBLE,
  "price" DOUBLE,
  "site_location" VARCHAR
);