Searching for the right fashion datasets can be a daunting task, especially if you’re new to data science or looking for inspiration for your next project. To make your journey easier, we’ve curated a collection of open-source fashion datasets that will give you a valuable glimpse into the world of fashion data analytics.
I’ve categorised these datasets into four main sections: Product Listings, Product Reviews, Image Data, and Text Data. Each dataset comes with a brief description and a link to its source.
Please note:
We’ll continually update this resource, and we welcome contributions. If you have more fashion dataset sources to share, please leave a comment or send them to info@data4fashion.org.
Let’s dive into the datasets!
Product Listings
This dataset includes information on over 1500 Adidas fashion products. It contains 21 columns with variables like name, selling price, original price, currency, availability, colour, brand, country, average rating, and review count. Ideal for fashion retail analysis.
A dataset that features 3268 products from Nike and Adidas. With 10 columns, it covers fields such as ratings, discounts, sales price, listed price, product description, and the number of reviews. Perfect for clustering and competitor analysis.
A dataset with 17 columns and 10,000 rows providing details on unique IDs, prices, reviews, manufacturers, and more.
A relatively small dataset with 4 columns, including weight, age, height, and size. It’s suitable for predicting clothing sizes for online purchases.
Scraped from an online C2C fashion store with over 9 million registered users, this dataset consists of 98,913 rows and 27 columns, covering information like country, language, products sold, gender, and more.
Comprising 8 columns and 12,000 products from Myntra, a major Indian fashion e-commerce site.
This dataset includes both an image and a CSV file with headers like gender, season, year, and colour. It’s suitable for image classification and product analysis.
With 395 rows, this dataset provides product listings from Gymboree.
Includes product information and images, focusing on the purchase history of customers over time.
Featuring Myntra’s product listings, this dataset has 11 columns with headers like price, name, color, brand, rating, and more.
Focusing on men’s fashion items in Myntra’s product listings.
This dataset contains comprehensive information about products available in the men’s t-shirt section on myntra.com. It includes details like price, brand, discount, and more.
A CSV file with 10 columns, featuring information like SKU, price, product name, and product availability.
A dataset on Nike US fashion products with 17 fields, covering details like name, subtitle, brand, model, color, price, currency, availability, description, and more.
This dataset contains summer-related products available for sale as of July 2020. With 43 columns, it includes information such as units sold, currency, ratings, and rating counts.
A list of 10,000 women’s shoes with various product information, including their prices.
Product Reviews
Customer feedback on the items purchased.
This dataset includes product reviews written by customers.
Image Datasets
Text Datasets
The following datasets contain fashion images suitable for computer vision, product recommendation, and other deep-learning projects:
19. Clothing Dataset (Git Hub)
20. Clothing Dataset
21. Clothes Segmentation Dataset
22. Fashion Product Images Dataset
23. Nike and Adidas Shoes for Image Dataset
24. Product Images
25. Zalando Fashion-mnist
For Natural Language Processing (NLP) projects, here are a few text datasets:
26. Nike Just Do it Tweets
27. Fashion Conversation Data on Instagram
And that’s a wrap! This resource will be continuously updated and open to contributions. Share your experiences with these datasets in the comments section, and if you have any questions or suggestions, please don’t hesitate to let us know.
In Conclusion
This post offers as a good opening to a variety of fashion datasets, providing data science enthusiasts with a treasure trove of possibilities. It is intended to remain an evolving and improving resource, with a commitment to continual updates and an open welcome for community contributions.
These versatile datasets are useful for a wide range of data science applications, from retail analysis to computer vision and natural language processing (NLP), making them excellent tools for students and professionals in a variety of fields. Let this article serve as your compass as you engage in your fashion data adventures, guiding you through the constantly evolving field of data-driven fashion analysis.
Have fun exploring!
Recommended Dataset Sources
About the Author
Kiitan Olabiyi is a Fashion Data Consultant and Content Writer at DATA4FASHION.
She writes about data analytics application in fashion, technical tutorials and fashion trend analysis.
Connect with her on LinkedIn.
For inquiries on how to contribute to our fashion data blog, email us at info@data4fashion.org.
