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Amazon products
Consumer Electronics Usage
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About
This dataset includes product information for a collection of Products on Indian Amazon. It provides details on product features, pricing, discounts, ratings, and more, offering a valuable resource for analysing consumer preferences, market trends, and pricing strategies.
Dataset Features:
- AP_ID: Unique identifier for each product.
- Name: Product name, including specifications such as tonnage, star rating, cooling technology, and additional features.
- Main Category: The overall category to which the product belongs, such as appliances.
- Sub-category: A specific type of product, in this case, air conditioners.
- Image: URL linking to the product's image on Amazon.
- Link: URL linking to the product page on Amazon.
- Ratings: Average user ratings for the product, based on a scale of 1 to 5.
- Number of Ratings: Total number of users who rated the product.
- Discount Price (INR): The current selling price of the product.
- Actual Price (INR): The original price of the product without discounts.
Usage:
The dataset is ideal for a range of analyses and applications, including:
- Studying market trends and consumer behaviour.
- Training machine learning models for price prediction or demand forecasting.
- Benchmarking similar products based on user ratings and pricing.
- Analysing the relationship between product features and pricing strategies.
Coverage:
This dataset focuses on different types of products on the Indian Amazon. It covers essential aspects like price, category, and product name.
License:
CC0 (Public Domain)
Who Can Use It:
This dataset is suitable for data scientists, e-commerce analysts, market researchers, and students who want to explore consumer electronics and pricing patterns.
How to Use It:
- Product Analysis: Compare ratings, prices, and features to identify trends in consumer preferences.
- Machine Learning Models: Build models for price prediction or product recommendation.
- Market Research: Analyse the impact of discounts, star ratings, and brand reputation on purchasing decisions.
- Feature Correlation: Study the relationship between energy efficiency, tonnage, and price.
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