This dataset provides extensive information on cosmetic ingredients, their safety, and regulatory status based on European Union (EU) cosmetics regulations. It includes detailed lists of substances prohibited, restricted, and allowed in cosmetic products, along with specific colorants, preservatives, and UV filters permitted for use. The data is derived from the EU's Cosmetic Ingredient (CosIng) database, offering valuable insights for cosmetic formulators, researchers, and regulatory professionals.

This curated dataset contains only products from CultBeauty.com that include detailed ingredient information, ideal for brands, formulators, analysts, and researchers seeking transparency in cosmetics and skincare data.

It focuses on ingredient-rich listings — allowing deep analysis of formulation trends, compliance mapping, and clean beauty initiatives. Whether you're building an internal database or powering an AI model, this dataset offers a clean, structured foundation for insight.

What’s Included:

• Product Name

• Brand

• Full Ingredient List

• Category

• Product URL

• Price (if available)

• Description

• Image links

• Timestamps

Use Cases:

• Ingredient analysis for clean beauty scoring

• Competitor formulation comparison

• Cosmetic safety mapping (e.g., for allergen research)

• Building training sets for AI/ML models in skincare

• Trend monitoring across skincare and cosmetic products

Update Frequency:

Monthly or on demand

Inventory of Cosmetic Ingredients as amended by Decision 2006/257/EC establishing a common nomenclature of ingredients employed for labelling cosmetic products throughout the EU.

The Inventory is purely indicative and does not constitute a list of substances authorised for use in cosmetic products. An ingredients assigned with an INCI name that appears in the inventory section of CosIng does not mean it is to be used in cosmetic products nor approved for such use.

The inventory is divided into 2 sections:

•Section 1 – cosmetic ingredients other than perfume and aromatic raw materials;

•Section 2 – perfume and aromatic raw materials.

The inventory contains information concerning the identity of the ingredient, notably the INCI (ex CFTA), Ph. Eur., INN, IUPAC, and chemical names; and the EINECS/ELINCS, CAS; ingredients’ functions and any mandatory restrictions, conditions of use, and warnings.

About this Data

This is a list of 10,000 different food listings and their ingredients provided by Datafiniti's Product Database. The dataset includes the brand, name, manufacturer, category, features, and more for each product.

Note that this is a sample of a large dataset. The full dataset is available through Datafiniti.

What You Can Do With This Data

A similar dataset was used to determine if it's cheaper to eat in or eat out. Discover insights into ingredients used in various foods. E.g.:

• What's the distribution of the number of ingredients per listing?
• What are the most common ingredients used?
• What is the total cost of ingredients needed for a homemade meal versus restaurant meal?

Data Schema

A full schema for the data is available in our support documentation.

About Datafiniti

Datafiniti provides instant access to web data. We compile data from thousands of websites to create standardized databases of business, product, and property information. Learn more.

Interested in the Full Dataset?

Get this data and more by creating a free Datafiniti account or requesting a demo.

These data reflect information that has been reported to the California Safe Cosmetics Program (CSCP) in the California Department of Public Health (CDPH). The primary purpose of the CSCP is to collect information on hazardous and potentially hazardous ingredients in cosmetic products sold in California and to make this information available to the public.

For all cosmetic products sold in California, the California Safe Cosmetics Act (“the Act”) requires the manufacturer, packer, and/or distributor named on the product label to provide to the CSCP a list of all cosmetic products that contain any ingredients known or suspected to cause cancer, birth defects, or other developmental or reproductive harm.

To assist companies with reporting, CDPH has compiled a list of reportable ingredients based on lists and reports available from the authoritative scientific bodies cited in the Act to cause cancer or reproductive harm; it is meant to serve as guidance and is not all-inclusive. Companies with reportable ingredients in their products must submit information to the California Safe Cosmetics Program if the company:

• Has annual aggregate sales of cosmetic products of one million dollars or more, and
• Has sold cosmetic products in California on or after January 1, 2007.

The data table consists of: label names of cosmetic/personal care products, company/manufacturer names, product brand names, product categories, Chemical Abstracts Service registry numbers (CAS#) of the reported chemical ingredients, names of reported chemical ingredients, the number of reported chemicals for each product, and dates of reporting, product discontinuation or reformulation if applicable.

All products containing carcinogens or developmental or reproductive toxicants may not be included due to companies failing to report.

List of reportable ingredients: www.cdph.ca.gov/ReportableIngredientsList

Context

If you're in Northern California, you'll be walking past the inevitable bushels of leafy greens, spiked with dark purple kale and the bright pinks and yellows of chard. Across the world in South Korea, mounds of bright red kimchi greet you, while the smell of the sea draws your attention to squids squirming nearby. India’s market is perhaps the most colorful, awash in the rich hues and aromas of dozens of spices: turmeric, star anise, poppy seeds, and garam masala as far as the eye can see. Some of our strongest geographic and cultural associations are tied to a region's local foods.

This dataset was featured in our completed playground competition entitled What's Cooking? The objective of the competition was to predict the category of a dish's cuisine given a list of its ingredients.

Content

The data are stored in JSON format.

• train.json - the training set containing recipes id, type of cuisine, and list of ingredients

• test.json - the test set containing recipes id, and list of ingredients

An example of a recipe node in train.json can be found here or in the file preview section below.

Acknowledgements

This unique dataset was provided by Yummly and featured in a Kaggle playground competition for fun and practice. Visit the competition page if you are interested in checking out past discussions, competition leaderboard, or more details regarding the competition. If you are curious to see how your results rank compared to others', you can still make a submission at the competition submission page!

Open Food Facts Database

  What is 🍊 Open Food Facts?





  A food products database

Open Food Facts is a database of food products with ingredients, allergens, nutrition facts and all the tidbits of information we can find on product labels.

  Made by everyone

Open Food Facts is a non-profit association of volunteers. 25.000+ contributors like you have added 1.7 million + products from 150 countries using our Android or iPhone app or their camera to scan… See the full description on the dataset page: https://huggingface.co/datasets/openfoodfacts/product-database.

The Inactive Ingredient Database provides information on inactive ingredients present in Food and Drug Administration (FDA) approved drug products. This information can be used by industry as an aid in developing drug products.

A team of experts and scholars is formed to review genetically modified food ingredients on a case-by-case basis. This dataset allows for the inquiry of approved genetically modified food ingredients.

Gain insights into Amazon’s beauty and personal care market with this comprehensive Amazon Beauty Products Dataset. Covering 47,000 records across skincare, haircare, and makeup, this dataset provides full ingredient lists, product descriptions, pricing, and availability. Ideal for researchers and businesses focused on ingredient transparency, beauty trend analysis, and competitive market insights. Perfect for applications in ingredient research, product development, and e-commerce analysis.

Access a rich Amazon Beauty & Cosmetics dataset with over 47,000+ product records, including detailed ingredients.
Explore more on our Beauty & Cosmetics Data page or view the full Amazon Beauty Dataset

Walmart product dataset featuring detailed ingredient information across categories like beauty, food, personal care, and more.
View Dataset →

The dataset includes the following fields:

• ASIN: Unique Amazon product identifier.
• Product Name and Description: Full titles and descriptions of each product.
• Price and Availability: Current pricing and stock status.
• Categories: Product type classification (e.g., skincare, haircare, makeup).
• Ingredients: Complete ingredient lists, ensuring transparency about product composition.
• Images: High-quality product images.
• Brand and Manufacturer Information: Details of the brand and manufacturer.
• Customer Ratings and Reviews: User-generated content for understanding product popularity and performance.

This dataset is invaluable for:

• Ingredient Analysis: Understanding popular ingredients in beauty products.
• Market Research: Analyzing trends in beauty products, such as ingredient types and product categories.
• Competitive Analysis: Assessing product offerings by brand, price, and ingredients.

Whether you’re focused on skincare, haircare, makeup, or other beauty categories, this dataset provides in-depth information for deep analysis. For any custom requirements or additional data needs, please feel free to reach out.

This dataset contains meticulously extracted information on 100+ skincare products from Dermstore, one of the leading online skincare retailers. Designed for beauty analysts, researchers, and data scientists, this dataset provides a deep dive into ingredient compositions, product categories, and targeted skin concerns. Each entry is enriched with essential details, including full ingredient lists, enabling in-depth ingredient analysis and skincare product comparisons.

Data Highlights:

• Ingredient Listings: Comprehensive ingredient details for each product, ideal for ingredient-based research and analysis.
• Product and Brand Details: Product name, brand, category (e.g., cleansers, serums, sunscreens), and skin concerns (such as acne, aging, or sensitivity) offer full product context.
• User Ratings and Reviews (where available): Consumer ratings add valuable insights into product performance, satisfaction, and ingredient effectiveness.

Dataset Scope: The data includes essential product details and ingredient information for a variety of skincare products available on Dermstore. It covers skincare categories such as moisturizers, cleansers, serums, and sunscreens, making it a versatile tool for anyone interested in the ingredients behind skincare.

Dataset Use Cases:

1. Trend Analysis: Identify ingredient trends, such as the popularity of specific actives like hyaluronic acid, niacinamide, or retinol.
2. Recommendation Models: Build recommendation algorithms for skincare products based on ingredient compatibility and skin concerns.
3. Product Comparison: Conduct comparative studies on products with similar or unique ingredients.
4. Health and Safety Analysis: Research ingredient safety, allergens, and natural vs. synthetic composition trends.

Ideal For:

• Data Scientists: For projects in predictive modeling, trend analysis, and building recommendation systems.
• Beauty and Health Researchers: For ingredient efficacy studies, consumer trend analysis, and product formulation research.
• Skincare Enthusiasts: Provides insights into product compositions and ingredient effectiveness.

Contains a wide variety of ingredient substitutions for different recipes based on specific dietary preferences, such as vegan, low-calorie, gluten-free, and more. The data was compiled from multiple culinary sources, including popular recipe sites, cooking blogs.

Ingredients: This contains a list of ingredients in the recipe (e.g., ["semisweet chocolate", "sugar", "heavy cream", ...]).

Keywords: This contains dietary labels and preferences (e.g., ["contains dairy", "contains eggs", "shellfish free", ...]).

Cuisine: This represents the cuisine type (e.g., "Italian", "Mexican", or "nan" if not available)

The Dietary Supplement Ingredient Database (DSID) provides estimated levels of ingredients in dietary supplement products sold in the United States. The DSID data are reported by ingredient type and ingredient level for each product category.

This dataset contains a curated list of international foods along with their key ingredients. It is designed to help researchers, chefs, and food enthusiasts explore diverse cuisines and their core components. Each row represents a unique dish, and the corresponding column details its ingredients. The dataset can be used for culinary analysis, recipe generation, dietary studies, or machine learning projects related to food and nutrition.

Dataset of all the wonders of the world when it comes to food composition. Dishes ranging from a bread to a Swedish midsommer smorgasbord.

Some intersting things to know before starting: - There are duplicate dishes but the majority has a different recipe. - I have removed all duplicates in "NER" and made them all lowercase - Some of the columns are arrays, use df.apply and import Json to work with them. Check out the code in my notebook

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F10179217%2Fff93e5e3e0876fbb0298c780e1d4e342%2FWordcloud.png?generation=1687898448282120&alt=media" alt="">

Link to original: https://clickhouse.com/docs/en/getting-started/example-datasets/recipes

Try it with SQL: https://play.clickhouse.com/play?user=play#U0VMRUNUCiAgICBhcnJheUpvaW4oTkVSKSBBUyBrLAogICAgY291bnQoKSBBUyBjCkZST00gcmVjaXBlcwpHUk9VUCBCWSBrCk9SREVSIEJZIGMgREVTQwpMSU1JVCA1MA==

Terms and Conditions

I (the "Researcher") have requested permission to use the RecipeNLG dataset (the "Dataset") at Poznań University of Technology (PUT). In exchange for such permission, Researcher hereby agrees to the following terms and conditions:

1. Researcher shall use the Dataset only for non-commercial research and educational purposes.
2. PUT makes no representations or warranties regarding the Dataset, including but not limited to warranties of non-infringement or fitness for a particular purpose.
3. Researcher accepts full responsibility for his or her use of the Dataset and shall defend and indemnify PUT, including its employees, Trustees, officers and agents, against any and all claims arising from Researcher's use of the Dataset including but not limited to Researcher's use of any copies of copyrighted images or text that he or she may create from the Dataset.
4. Researcher may provide research associates and colleagues with access to the Dataset provided that they first agree to be bound by these terms and conditions.
5. If Researcher is employed by a for-profit, commercial entity, Researcher's employer shall also be bound by these terms and conditions, and Researcher hereby represents that he or she is fully authorized to enter into this agreement on behalf of such employer.

This document describes the use of the Natural Health Products Ingredients Database Issue Form, which is designed to help applicants send NHPID data requests which are complete and accurate.

The Dietary Supplement Ingredient Database (DSID) provides estimated levels of ingredients in dietary supplement products sold in the United States. These statistically predicted estimates may differ from labeled amounts and are based on chemical analysis of nationally representative products. The DSID was developed by the Nutrient Data Laboratory, US Department of Agriculture, in collaboration with the Office of Dietary Supplements at the National Institutes of Health (NIH) and other federal agencies. DSID-4 reports national estimates of ingredient content in adult, children’s and non-prescription prenatal multivitamin/mineral (MVMs) and omega-3 fatty acid supplements. New! Analytically-validated mean estimates for vitamin D, vitamin A and chromium in adult MVMs are reported for the first time, and estimates for 18 other ingredients have been calculated based on a new, second study of representative adult MVMs. DSID-4 also reports results for the first DSID study of botanical dietary supplements. The “Green Tea Research Summary and Results" are available on the 'Botanicals' page. The DSID is intended primarily for research applications. These data are appropriate for use in population studies of nutrient intake rather than for assessing content of individual products. Resources in this dataset:Resource Title: The Dietary Supplement Ingredient Database (DSID), Release 4. File Name: Web Page, url: https://dietarysupplementdatabase.usda.nih.gov/ provides estimated levels of ingredients in dietary supplement products sold in the United States. These statistically predicted estimates may differ from labeled amounts and are based on chemical analysis of nationally representative products. The DSID was developed by the Nutrient Data Laboratory, US Department of Agriculture, in collaboration with the Office of Dietary Supplements at the National Institutes of Health (NIH) and other federal agencies. DSID-4 reports national estimates of ingredient content in adult, children’s and non-prescription prenatal multivitamin/mineral (MVMs) and omega-3 fatty acid supplements.

Explore Indian Food Ingredients export data with HS codes, pricing, ports, and a verified list of Food Ingredients exporters and suppliers from India with complete shipment insights.

For over 30 years Mintec has been the leading provider of raw material market prices and analysis covering more than 14,000 food ingredients and non-food raw materials.

Ensuring they are best placed to reduce costs, manage risk and increase their efficiency, helping to maximise margins.

The Categories of coverage are: Beverages, Dairy & Eggs, Fish & Seafood, Food Ingredients, Fruit & Juices, Grains & Feed, Herbs Spices & Plants, Meat & Poultry, Nuts Seeds & Dried Fruit, Oilseeds Oils & Fats, Vegetables & Pulses. Chemicals, Economics, Energy & Transport, Industrial Materials, Metals & Ores, Plastics & Textiles, Pulp Paper & Wood.

From cost-modelling tools to price change reports, bespoke dashboards to custom alerts, our platform is designed to save time, reduce human error and drive more actionable and efficient outcomes.

Mintec enables the world's largest food, CPG, health & beauty and hospitality brands to implement more efficient & sustainable procurement strategies. Helping them to better track the price of their food ingredients and associated costs.

We do this by empowering our customers to better understand supplier prices, analyse their spend and negotiate with confidence to better control their costs.

This guide was developed to help users search and navigate the Natural Health Products Ingredients Database using the online Web application.