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Retail Market Basket Data
Data Science and Analytics
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About
This dataset is designed for Market Basket Analysis, specifically for association rules analysis using algorithms such as Apriori. Its primary purpose is to identify frequent itemsets within a retail sales context, providing insights into products commonly purchased together. The Apriori algorithm leverages prior knowledge of frequent itemset properties, employing an iterative, level-wise search to discover relationships between items. This dataset is a valuable resource for understanding purchasing patterns and informing retail strategies.
Columns
The dataset contains 17 columns, each representing a specific product. These columns are boolean in nature, indicating whether a particular item was present (
true) or absent (false) in a transaction.- Apple: Indicates information about apple sales. (383 true, 616 false)
- Bread: Indicates information about bread sales. (384 true, 615 false)
- Butter: Indicates information about butter sales. (420 true, 579 false)
- Cheese: Indicates information about cheese sales. (404 true, 595 false)
- Corn: Indicates information about corn sales. (407 true, 592 false)
- Dill: Indicates information about dill sales. (398 true, 601 false)
- Eggs: Indicates information about eggs sales. (384 true, 615 false)
- Ice cream: Indicates information about ice cream sales. (410 true, 589 false)
- Kidney Beans: Indicates information about kidney beans sales. (408 true, 591 false)
- Milk: Indicates information about milk sales. (405 true, 594 false)
- Nutmeg: Indicates information about nutmeg sales. (401 true, 598 false)
- Onion: Indicates information about onion sales. (403 true, 596 false)
- Sugar: Indicates information about sugar sales. (409 true, 590 false)
- Unicorn: Indicates information about unicorn sales. (389 true, 610 false)
- Yogurt: Indicates information about yogurt sales. (420 true, 579 false)
- chocolate: Indicates information about chocolate sales. (421 true, 578 false)
Distribution
The dataset is provided as a CSV file (
basket_analysis.csv), with a size of 93.46 kB. It comprises 17 columns and 999 valid records, with no mismatched or missing values across the listed product columns.Usage
This dataset is ideal for:
- Conducting Market Basket Analysis.
- Implementing and testing Apriori algorithms.
- Identifying frequent itemsets and boolean association rules.
- Developing and evaluating recommender systems.
- Exploring customer purchasing patterns in a retail setting.
Coverage
The dataset's geographic, time range, and demographic scope are not specified within the provided information.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Analysts: For exploring association rules, particularly with the Apriori algorithm.
- Retail Businesses: To understand customer purchasing habits, optimise product placement, and create targeted promotions.
- Researchers: Studying consumer behaviour and data mining techniques.
- Students: Learning about market basket analysis and algorithm implementation.
Dataset Name Suggestions
- Retail Market Basket Data
- Product Sales Association Dataset
- Apriori Retail Items
- Shopping Transaction Analysis
- Frequent Itemset Dataset
Attributes
Original Data Source: Retail Market Basket Data
QUALITY