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Housing Prices Dataset
This example loads the Housing Prices Dataset from a CSV file and displays the raw data as JSON in a pre element. The code uses D3 v7 functions such as `d3.select`, `d3.csvParse`, and the `join` operation to manage the data loading and DOM rendering. It demonstrates a straightforward approach to fetching, parsing, and visualizing tabular data, with the fetched CSV transformed into an array of objects for display.
AI-generated descriptionDataset 3: Housing Prices Dataset
Source:
Housing Prices Dataset
This dataset contains housing price records used for prediction and regression tasks. It includes a variety of features such as the size of the house, number of rooms, year built, and more, making it useful for exploratory data analysis, visualization, and machine learning projects.
Attributes and Types
Idβ Quantitative, nominal (unique identifier)MSSubClassβ Categorical, nominal (type of dwelling)MSZoningβ Categorical, nominal (general zoning classification)LotAreaβ Quantitative, ratio (lot size in square feet)Streetβ Categorical, nominal (type of road access)LotShapeβ Categorical, ordinal (general shape of property)YearBuiltβ Quantitative, interval (original construction date)OverallQualβ Quantitative, ordinal (overall material and finish quality)OverallCondβ Quantitative, ordinal (overall condition rating)GrLivAreaβ Quantitative, ratio (above ground living area in square feet)FullBathβ Quantitative, ratio (full bathrooms above grade)BedroomAbvGrβ Quantitative, ratio (number of bedrooms above grade)GarageCarsβ Quantitative, ratio (size of garage in car capacity)GarageAreaβ Quantitative, ratio (garage size in square feet)SalePriceβ Quantitative, ratio (target variable: sale price in USD)
MIT Licensed
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