--- dataset_info: features: - name: title dtype: string - name: average_rating dtype: float64 - name: rating_number dtype: int64 - name: features dtype: string - name: description dtype: string - name: price dtype: float64 - name: images list: - name: thumb dtype: string - name: large dtype: string - name: variant dtype: string - name: hi_res dtype: string - name: videos list: - name: title dtype: string - name: url dtype: string - name: user_id dtype: string - name: store dtype: string - name: categories sequence: 'null' - name: parent_asin dtype: string - name: upc dtype: string - name: brand dtype: string - name: manufacturer dtype: string - name: product_dimensions dtype: string - name: color dtype: string - name: material dtype: string - name: is_discontinued_by_manufacturer dtype: string - name: item_form dtype: string - name: item_model_number dtype: string - name: age_range_(description) dtype: string - name: skin_type dtype: string - name: scent dtype: string - name: package_dimensions dtype: string - name: hair_type dtype: string - name: unit_count dtype: string - name: number_of_items dtype: string splits: - name: train num_bytes: 35604373 num_examples: 18956 download_size: 17113574 dataset_size: 35604373 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for Dataset Name Original dataset can be found on: https://amazon-reviews-2023.github.io/ ## Dataset Details This dataset is downloaded from the link above, the category Amazon All Beauty meta dataset. ### Dataset Description This dataset is a refined version of the Amazon All Beauty 2023 meta dataset, which originally contained product metadata for beauty products sold on Amazon. The dataset includes detailed information about products such as their descriptions, ratings, prices, images, and features. The primary focus of this modification was to ensure the completeness of key fields while simplifying the dataset by removing irrelevant or empty columns. The table below represents the original structure of the dataset.

Field	Type	Explanation
main_category	str	Main category (i.e., domain) of the product.
title	str	Name of the product.
average_rating	float	Rating of the product shown on the product page.
rating_number	int	Number of ratings in the product.
features	list	Bullet-point format features of the product.
description	list	Description of the product.
price	float	Price in US dollars (at time of crawling).
images	list	Images of the product. Each image has different sizes (thumb, large, hi_res). The “variant” field shows the position of image.
videos	list	Videos of the product including title and url.
store	str	Store name of the product.
categories	list	Hierarchical categories of the product.
details	dict	Product details, including materials, brand, sizes, etc.
parent_asin	str	Parent ID of the product.
bought_together	list	Recommended bundles from the websites.

### Modifications Made

Products without a description, title, or images were removed.
The column main_category was dropped due to lack of informative content. The column bought_together was entirely empty, so it was also removed.
For the details column, only the top 16 most frequent detail types were kept. Products with empty details fields were excluded from the final dataset. The details column was then split into these new 16 columns based on the detail types kept.

### Dataset Size

Total entries: 18,956
Total columns: 27

### Final structure

Field	Type	Explanation
title	str	Name of the product.
average_rating	float	Rating of the product shown on the product page.
rating_number	int	Number of ratings in the product.
features	list	Bullet-point format features of the product.
description	list	Description of the product.
price	float	Price in US dollars (at time of crawling).
images	list	Images of the product. Each image has different sizes (thumb, large, hi_res). The “variant” field shows the position of image.
videos	list	Videos of the product including title and url.
store	str	Store name of the product.
details	dict	Product details, including materials, brand, sizes, etc.
parent_asin	str	Parent ID of the product.
upc	str	Universal Product Code (UPC), a barcode for uniquely identifying the product.
brand	str	Brand name associated with the product.
manufacturer	str	Name of the company or manufacturer responsible for producing the product.
product_dimension	str	Dimensions of the product, typically including length, width, and height.
color	str	Primary color or color variants of the product.
material	str	Main materials used in the product’s construction.
is_discontinued_by_manufacturer	str	Indicates whether the product has been discontinued by the manufacturer.
item_form	str	Form of the item (e.g., liquid, solid, gel).
item_model_number	str	Model number of the product as assigned by the manufacturer.
age_range_(description)	str	Recommended age range for the product, often used for toys or children’s products.
skin_type	str	Suitable skin types for the product (e.g., oily, dry, sensitive).
scent	str	Fragrance or scent associated with the product.
package_dimensions	str	Dimensions of the product’s packaging.
hair_type	str	Suitable hair types for the product (e.g., curly, straight, fine).
unit_count	str	Total quantity or units contained in the product package.
number_of_items	str	Total number of individual items in the product package.