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About Dataset
The rapid growth of e-commerce has transformed how consumers shop. While some customers fully embrace online shopping, others still prefer visiting physical stores, and many adopt a hybrid approach.
This dataset simulates real-world consumer behaviour by combining demographic information, digital habits, shopping patterns, logistics preferences, and psychological factors.
The goal is to help data scientists and analysts:
Explore shopping behaviour trends
Perform exploratory data analysis (EDA)
Build classification models
Understand factors influencing shopping channel preference
The dataset contains 11,789 records and 26 features, designed to provide realistic patterns and balanced class distribution for machine learning projects.
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