--- dataset_info: features: - name: main_category dtype: string - 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: string - name: parent_asin dtype: string - name: manufacturer dtype: string - name: upc dtype: string - name: product_dimensions dtype: string - name: item_model_number dtype: string - name: unit_count dtype: string - name: item_weight dtype: string - name: brand dtype: string - name: item_form dtype: string - name: color dtype: string - name: package_dimensions dtype: string - name: age_range_(description) dtype: string - name: material dtype: string - name: hair_type dtype: string - name: scent dtype: string - name: skin_type dtype: string splits: - name: train num_bytes: 1278565618 num_examples: 554058 download_size: 603060217 dataset_size: 1278565618 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 Beauty and Personal Care meta dataset. ### Dataset Description This dataset is a refined version of the Amazon Beauty and Personal Care 2023 meta dataset, which originally contained product metadata for products that are intended for beauty and personal care that are 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, images or details were removed.
Lists in features and description are transformed into strings concatinated with a newline
For the details column, only the top 16 most frequent detail types were kept. The details column was then split into these new 16 columns based on the detail types kept.
Products with date first available before the year 2015 are dropped.
Products with is_discontinued_by_manufacturer set to 'true' or 'yes' are dropped. Then that column was dropped.
Column bought_together is dropped due to missing values.

### Dataset Size

Total entries: 554,058
Total columns: 27

### Final Structure

Field	Type	Explanation
main_category	str	Main category
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.
manufacturer	str	Manufacturer
upc	str	Universal Product Code (UPC), a barcode for uniquely identifying the product.
product_dimensions	str	Dimensions of the product
item_model_number	str	Model number of the item
unit_count	str	Total quantity or units contained in the product package.
item_weight	str	Weight of the item
brand	str	Brand
item_form	str	Item form
color	str	Color
package_dimensions	str	Package dimensions
age_range_(description)	str	Age range
material	str	Material
Suitable hair types for the product (e.g., curly, straight, fine).	str	Hair type
scent	str	Fragrance or scent associated with the product.
skin_type	str	Suitable skin types for the product (e.g., oily, dry, sensitive).