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E-commerce Behaviour Analysis Dataset
E-commerce & Online Transactions
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Free
About
This dataset features 50,000 fictional e-commerce transaction records. It is designed for various data analysis, visualisation, and machine learning experiments. The dataset includes details such as user demographics, product categories, purchase amounts, payment methods, and transaction dates. Its primary purpose is to help in understanding consumer behaviour and identifying sales trends. Being synthetic, it does not contain any real user data, making it well-suited for research, experimentation, and educational applications.
Columns
- Transaction_ID: A unique identifier assigned to each individual transaction.
- User_Name: A randomly generated name for the user involved in the transaction.
- Age: The age of the user, ranging from 18 to 70 years.
- Country: The country where the transaction occurred, selected randomly from a list of 10 countries.
- Product_Category: The category of the item purchased, such as Electronics, Clothing, or Books.
- Purchase_Amount: The total monetary value of the transaction, randomly generated between $5 and $1000.
- Payment_Method: The method used for payment, including options like Credit Card, PayPal, or UPI.
- Transaction_Date: The date of the purchase, randomly selected from within the past two years.
Distribution
The dataset is provided in a CSV format and contains 50,000 fictional e-commerce transaction records. It includes 8 distinct columns. The file size is approximately 3.32 MB.
Usage
This dataset is ideal for a variety of analytical tasks and projects:
- Sales and trend analysis: Useful for identifying which product categories are most popular over time.
- Customer segmentation: Enables the analysis of spending behaviour based on user age and country.
- Fraud detection: Can be used to detect unusual purchase patterns.
- Machine learning projects: Suitable for training models for recommendation systems or revenue prediction.
Coverage
The dataset's coverage includes:
- Geographic Scope: Transactions originate from 10 randomly selected countries.
- Time Range: Transaction dates are randomly distributed within a two-year period, specifically from March 2023 to March 2025.
- Demographic Scope: User ages range from 18 to 70 years. All user data, including names, are randomly generated and fictional.
License
CC0: Public Domain
Who Can Use It
This dataset is beneficial for:
- Data Analysts: For visualising sales trends and consumer purchasing habits.
- Researchers: For studying consumer behaviour patterns without using real-world sensitive data.
- Students: For educational purposes, learning data manipulation, analysis, and statistical methods.
- Machine Learning Engineers: For developing and testing models related to recommendations, predictions, and anomaly detection.
Dataset Name Suggestions
- Synthetic E-commerce Transactions
- Fictional Consumer Purchase Data
- Online Retail Transaction Records
- E-commerce Behaviour Analysis Dataset
- Digital Sales Activity Log
Attributes
Original Data Source: E-commerce Behaviour Analysis Dataset
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