--- 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: date_first_available dtype: int64 - name: department dtype: string - name: manufacturer dtype: string - name: item_model_number dtype: string - name: product_dimensions dtype: string - name: item_weight dtype: string - name: color dtype: string - name: brand dtype: string - name: size dtype: string - name: best_sellers_rank dtype: string - name: package_dimensions dtype: string - name: material dtype: string - name: style dtype: string - name: age_range_(description) dtype: string - name: country_of_origin dtype: string splits: - name: train num_bytes: 6001681637 num_examples: 2539634 download_size: 2552518590 dataset_size: 6001681637 configs: - config_name: default data_files: - split: train path: data/train-* --- # Amazon Clothing Shoes and Jewelry 2023 Dataset Original dataset can be found on: https://amazon-reviews-2023.github.io/ ## Dataset Details This dataset is downloaded from the link above, the category Clothing Shoes and Jewelry meta dataset. ### Dataset Description The Amazon Clothing Shoes and Jewelry 2023 dataset provides information on products from a diverse ranger of categories, including main attributes like ratings, price, and desciptions. 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.
Column bought_together is dropped due to missing values.

### Dataset Size

Total entries: 2 539 634
Total columns: 27

### Final structure

Field	Type	Explanation
main_category	string	Primary product 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.
categories	list[str]	Subcategories of the product.
parent_asin	str	Parent ID of the product.
date_first_available	timestamp	First date when the product was available.
department	string	Department of the product. (E.g. womens, mens)
country_of_origin	string	Name of the country of origin
item_weight	string	Weight of the product in ounces or pounds.
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_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.
size	str	Size of product
best_sellers_rank	string	Amazon best-sellers rank
package_dimensions	string	Package dimensions
style	string	Style

### Usage ## Download the dataset ```ruby dataset = load_dataset("smartcat/Amazon_Clothing_Shoes_and_Jewelry_2023", split="train") ```