Dataset: House Price Prediction Treated Dataset

About this Dataset

House Price Prediction Treated Dataset

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Same dataset as "House Sales in King County, USA", but with treated content and with a split version (train-test) allowing direct use in machine learning models.

We have 14 columns in the dataset, as it follows:

date: Date of the home sale
price: Price of each home sold
bedrooms: Number of bedrooms
bathrooms: Number of bathrooms
living_in_m2: Square meters of the apartments interior living space
nice_view: A flag that indicates the view's quality of a property
perfect_condition: A flag that indicates the maximum index of the apartment condition
grade: An index from 1 to 5, where 1 falls short of quality level and 5 have a high quality level of construction and design
has_basement: A flag indicating whether or not a property has a basement
renovated: A flag if the property was renovated
has_lavatory: Check for the presence of these incomplete/secondary bathrooms (bathtub, sink, toilet)
single_floor: A flag indicating whether the property had only one floor
month: The month of the home sale
quartile_zone: A quartile distribution index of the most expensive zip codes, where 1 means less expansive and 4 most expansive.

Tables

Df Test

@kaggle.aravinii_house_price_prediction_treated_dataset.df_test

64.17 KB
6700 rows
14 columns


CREATE TABLE df_test (
  "date" TIMESTAMP,
  "price" DOUBLE,
  "bedrooms" BIGINT,
  "grade" BIGINT,
  "has_basement" BOOLEAN,
  "living_in_m2" DOUBLE,
  "renovated" BOOLEAN,
  "nice_view" BOOLEAN,
  "perfect_condition" BOOLEAN,
  "real_bathrooms" BIGINT,
  "has_lavatory" BOOLEAN,
  "single_floor" BOOLEAN,
  "month" BIGINT,
  "quartile_zone" BIGINT
);

Df Train

@kaggle.aravinii_house_price_prediction_treated_dataset.df_train

113.49 KB
13603 rows
14 columns


CREATE TABLE df_train (
  "date" TIMESTAMP,
  "price" DOUBLE,
  "bedrooms" BIGINT,
  "grade" BIGINT,
  "has_basement" BOOLEAN,
  "living_in_m2" DOUBLE,
  "renovated" BOOLEAN,
  "nice_view" BOOLEAN,
  "perfect_condition" BOOLEAN,
  "real_bathrooms" BIGINT,
  "has_lavatory" BOOLEAN,
  "single_floor" BOOLEAN,
  "month" BIGINT,
  "quartile_zone" BIGINT
);