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House Prices 2023 Dataset

This dataset is about Pakistan Houses. The dataset is from Zameen.com website.

@kaggle.howisusmanali_house_prices_2023_dataset

About this Dataset

House Prices 2023 Dataset

Property id The unique value of each Property.
Location id The unique value of each location is based on the subcategory of the city.
Page URL The URL of the page where the property was published.
Property type In this section we have six different types:

  1. House
  2. FarmHouse
  3. Upper Portion
  4. Lower Portion
  5. Flat
  6. Room

Price Price is a dependent feature/parameter in this dataset.
City In this dataset the total number of cities is five:

  1. Lahore
  2. Karachi
  3. Faisalabad
  4. Rawalpindi
  5. Islamabad

Province Province parameter is about the state of the city
Location It is about the different kinds of locations in each city.
Lastly, the Latitude and Longitude of the Cities.

Tables

Cleaned Data For Model

@kaggle.howisusmanali_house_prices_2023_dataset.cleaned_data_for_model
  • 1.06 MB
  • 99499 rows
  • 9 columns
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CREATE TABLE cleaned_data_for_model (
  "unnamed_0" BIGINT,
  "property_type" VARCHAR,
  "price" BIGINT,
  "location" VARCHAR,
  "city" VARCHAR,
  "baths" BIGINT,
  "purpose" VARCHAR,
  "bedrooms" BIGINT,
  "area_in_marla" DOUBLE
);

For Eda Dataset

@kaggle.howisusmanali_house_prices_2023_dataset.for_eda_dataset
  • 2.92 MB
  • 153430 rows
  • 15 columns
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CREATE TABLE for_eda_dataset (
  "unnamed_0" BIGINT,
  "property_type" VARCHAR,
  "price" BIGINT,
  "location" VARCHAR,
  "city" VARCHAR,
  "province_name" VARCHAR,
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "baths" BIGINT,
  "purpose" VARCHAR,
  "bedrooms" BIGINT,
  "date_added" TIMESTAMP,
  "agency" VARCHAR,
  "agent" VARCHAR,
  "area_in_marla" DOUBLE
);

House Price Dataset

@kaggle.howisusmanali_house_prices_2023_dataset.house_price_dataset
  • 9.1 MB
  • 168446 rows
  • 20 columns
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CREATE TABLE house_price_dataset (
  "property_id" BIGINT,
  "location_id" BIGINT,
  "page_url" VARCHAR,
  "property_type" VARCHAR,
  "price" BIGINT,
  "location" VARCHAR,
  "city" VARCHAR,
  "province_name" VARCHAR,
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "baths" BIGINT,
  "area" VARCHAR,
  "purpose" VARCHAR,
  "bedrooms" BIGINT,
  "date_added" VARCHAR,
  "agency" VARCHAR,
  "agent" VARCHAR,
  "area_type" VARCHAR,
  "area_size" DOUBLE,
  "area_category" VARCHAR
);