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Kansas City Home Pricing Dataset
Data Science and Analytics
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About
This collection of house data from Kansas City explores the fundamental trends governing property prices, focusing on metrics such as location, construction specifications, and interior size. It is a valuable resource for identifying factors that significantly contribute to the fluctuation and general upward movement of home prices in the region. The data is suitable for detailed Exploratory Data Analysis and for building predictive models related to the housing market.
Columns
The dataset contains 22 self-explanatory data fields:
- id: A unique identifier assigned to each home sale record.
- date: The specific date when the property sale occurred.
- price: The final sale price of the home.
- bedrooms: The total count of bedrooms in the property.
- bathrooms: The total count of bathrooms; note that .5 represents a room with a toilet but no shower facility.
- sqft_living: The interior living space, measured in square footage.
- sqft_lot: The size of the land space surrounding the property, measured in square footage.
- floors: The number of floors in the house.
- waterfront: A binary indicator (dummy variable) noting if the property overlooks the waterfront.
- view: An index score ranging from 0 to 4, indicating the quality of the property's view.
- condition: An index score ranging from 1 to 5, reflecting the overall condition of the apartment.
- grade: An index from 1 to 13, where scores 1-3 indicate construction and design falling short of standards, 7 is considered average, and 11-13 represent high-quality construction.
- sqft_above: The square footage of the interior housing space located above ground level.
- sqft_basement: The square footage of the interior housing space located below ground level.
- yr_built: The year the house was initially constructed.
- yr_renovated: The year of the house’s most recent renovation (if applicable).
- zipcode: The postal code area in which the house is situated.
- lat: The property's latitude coordinate.
- long: The property's longitude coordinate.
- sqft_living15: The square footage of interior living space for the nearest 15 neighbours.
- sqft_lot15: The square footage of the land lots for the nearest 15 neighbours.
Distribution
The dataset is structured with 21,613 records across 22 columns, typically delivered in CSV format. Based on statistical summaries, the data appears highly clean, with zero percent missing or mismatched entries across the key fields. Sale dates span from May 2014 to May 2015.
Usage
This data is perfectly suited for several analytical tasks, including:
- Conducting Exploratory Data Analysis (EDA) to understand underlying relationships between features.
- Price analysis by area, leveraging latitude and longitude coordinates.
- Developing predictive models using techniques like Regression, Classification, or Clustering to forecast housing prices.
- Investigating annual fluctuations to determine the busiest times for sales and corresponding price spikes.
Coverage
The data focuses exclusively on Kansas City (KC) house sale records. The time frame for the sales captured ranges from 2 May 2014 to 27 May 2015. The construction years of the houses included span over a century, from 1900 up to 2015. The dataset is expected to be updated annually.
License
CC0: Public Domain
Who Can Use It
This resource is intended for a variety of users, particularly those categorized as beginners in data science, as well as:
- Data Scientists and Analysts focused on housing markets.
- Individuals performing geospatial analysis relating price to geographic factors.
- Researchers building machine learning models (Regression and Classification) to predict real estate value.
Dataset Name Suggestions
- Kansas City Home Pricing Dataset
- KC Housing Sale Records
- KC_House_Data (Original Title)
- Geospatial KC Real Estate
Attributes
Original Data Source: Kansas City Home Pricing Dataset
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