Perfume E-Commerce Dataset 2024

Dataset Overview

The Perfume E-Commerce Dataset 2024 comprises detailed information on 2000 perfume listings sourced from eBay, split into two separate CSV files for men's and women's perfumes, each containing 1000 entries. This dataset provides a comprehensive view of the current market trends, pricing, availability, and geographical distribution of perfumes in the e-commerce space.

Data Science Applications

This dataset offers numerous opportunities for data science applications, including but not limited to:

1. Market Analysis: Understand market trends and consumer preferences by analyzing the pricing and availability of different perfume brands and types.
2. Sales Prediction: Develop models to predict future sales based on historical data, aiding in inventory management and sales strategy optimization.
3. Customer Insights: Gain insights into customer preferences and behaviors by examining the data on sold quantities and item locations.
4. Price Optimization: Analyze price distributions and identify optimal pricing strategies to maximize revenue.
5. Geographical Distribution: Study the geographical distribution of listings to understand regional market dynamics and demand variations.

Column Descriptors

• brand: The brand of the perfume.
• title: The title of the listing.
• type: The type of perfume (e.g., Eau de Parfum, Eau de Toilette).
• price: The price of the perfume.
• priceWithCurrency: The price with currency notation.
• available: The number of items available.
• availableText: Text description of availability.
• sold: The number of items sold.
• lastUpdated: The last updated timestamp of the listing.
• itemLocation: The location of the item.

Ethically Mined Data

This dataset has been ethically mined from eBay using the Apify API, ensuring compliance with ethical data collection practices. The data is intended solely for educational and learning purposes. Users are encouraged to use the dataset responsibly and in accordance with applicable data usage policies.

Acknowledgements

• Apify: For providing the API used to scrape eBay data.
• DALL·E 3: For generating the thumbnail image used for this dataset.

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This dataset is a valuable resource for students, educators, and data science enthusiasts looking to explore and analyze e-commerce trends in the perfume industry.