E-Commerce Pet Supplies Dataset

Dataset Overview

The "E-Commerce Pet Supplies Dataset" offers a comprehensive snapshot of pet products sold on an online platform. This dataset includes 1,998 entries, each representing a unique pet supply product available for purchase. It is tailored for data science projects focused on e-commerce trends, product popularity, and consumer preferences within the pet supply market.

Data Science Applications

This dataset is ideal for several data science applications, including:

• Market Trend Analysis: Understanding popular products based on sales and customer wishes.
• Product Rating Analysis: Evaluating customer satisfaction through average star ratings.
• Inventory Management: Analyzing quantity data to optimize stock levels.
• Sales Prediction: Developing models to predict future sales based on existing data.

Column Descriptors

• title: The name or description of the pet supply product.
• averageStar: The average rating of the product, scaled from 0 to 5.
• quantity: The number of units available in stock.
• tradeAmount: The total number of units sold, presented in a string format like '5 sold' or '1,000+ sold'.
• wishedCount: The number of times customers have added the product to their wishlist.

Ethically Mined Data and No Personal Data/Information

This dataset is compiled using ethical mining practices with the assistance of Apify and does not contain any personal data or sensitive customer information, ensuring compliance with data protection standards.

Acknowledgements

We express our gratitude to Apify for facilitating the data collection and AliExpress for allowing access to the relevant e-commerce data. Additionally, we acknowledge DALL-E 3 for creating the thumbnail and cover images used for this dataset.

Usage

This dataset is provided for learning and educational purposes only. It should not be used for commercial purposes. Users are encouraged to use this data to enhance their understanding of e-commerce dynamics, specifically in the pet supply sector, and to develop data science skills related to real-world applications.