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Diamond Price Prediction Data
Stock & Market Data
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About
Contains data on the characteristics of diamonds, intended for building models to predict market prices. Each record represents a single diamond, detailed with various attributes such as weight, shape, colour, and dimensions. This information is ideal for creating predictive models or performing cluster analysis, particularly by examining objective variables rather than subjective quality measures like clarity.
Columns
- carat: The weight of the diamond, where one carat equals 200 milligrams.
- cut: A score representing the diamond's shape in terms of its marketability or "usability".
- color: The diamond's grade based on the international transparency scale.
- clarity: The grade of the diamond based on the number of impurities, following the international clarity scale.
- depth: A percentage value calculated as z / x, a standard industry parameter.
- table: A percentage value calculated from the z dimension and another variable not included in this dataset.
- price: The market price of the diamond in US Dollars.
- x: The 'x' dimension of the diamond in millimetres.
- y: The 'y' dimension of the diamond in millimetres.
- z: The 'z' dimension of the diamond in millimetres.
Distribution
The data is provided in a single CSV file named
DiamondsPrices.csv with a size of 2.45 MB. It is structured in a tabular format containing 53,900 records and 10 columns.Usage
This data is suitable for a range of applications, including:
- Developing machine learning models to predict diamond prices.
- Performing data analytics to understand the factors that influence diamond valuation.
- Clustering diamonds based on their physical characteristics.
- Educational purposes for individuals new to data analytics and predictive modelling.
Coverage
The dataset does not specify a geographic origin or a time range for the diamond data collected. It represents a general collection of diamonds with varied characteristics without specific demographic or temporal limitations.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: Can build and test regression models for price prediction.
- Data Analysts: Can explore relationships between a diamond's physical attributes and its market value.
- Students and Beginners: Ideal for learning fundamental data analysis and machine learning techniques on a clean, tabular dataset.
- Jewellery Industry Professionals: Can use the data for market analysis and pricing strategy development.
Dataset Name Suggestions
- Diamond Price Prediction Data
- Diamond Characteristics and Pricing
- Predictive Diamond Analytics
- Gemstone Attributes and Value
Attributes
Original Data Source: Diamond Price Prediction Data
QUALITY