Data
AutoDescDataset

AutoDescDataset

active ARFF Public Domain (CC0) Visibility: public Uploaded 17-03-2024 by Iwo Godzwon
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Description: The dataset contains information about various products, their stock levels, prices, and the locations where they are sold. Columns description: 1. Product: Represents the name of the product being sold, such as Milk, Coke, Water, etc. 2. Stock: Indicates the quantity of each product available in stock. 3. Price: Reflects the price of each product, possibly with negative values indicating discounts or losses. 4. Place: Denotes the location where the product is being sold, such as Birmingham or London. Use case: This dataset can be valuable for retailers, supply chain managers, and market analysts. Retailers can use the information on stock levels and prices to make strategic pricing and stocking decisions. Supply chain managers can optimize inventory levels based on product popularity and location demand. Market analysts can analyze sales trends across different locations to identify growth opportunities or areas needing improvement. Ultimately, this dataset can help businesses enhance their operational efficiency and maximize profits.

4 features

Productnominal5 unique values
0 missing
Stocknumeric73500 unique values
0 missing
Pricenumeric73503 unique values
0 missing
Placenominal2 unique values
0 missing

19 properties

73503
Number of instances (rows) of the dataset.
4
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
2
Number of numeric attributes.
2
Number of nominal attributes.
25
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
50
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
50
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
1
Number of binary attributes.

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