--- 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: manufacturer dtype: string - name: brand_name dtype: string - name: color dtype: string - name: package_weight dtype: string - name: item_package_dimensions_l_x_w_x_h dtype: string - name: part_number dtype: string - name: material dtype: string - name: best_sellers_rank dtype: string - name: size dtype: string - name: style dtype: string - name: brand dtype: string - name: suggested_users dtype: string - name: item_weight dtype: string - name: item_dimensions__lxwxh dtype: string - name: department dtype: string - name: sport_type dtype: string splits: - name: train num_bytes: 1293209275 num_examples: 535206 download_size: 607190296 dataset_size: 1293209275 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 Sports and Outdoors meta dataset. ### Dataset Description This dataset is a refined version of the Amazon Sports and Outdoors 2023 meta dataset, which originally contained product metadata for sports and outdoors products 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 ### Dataset Size ### 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.
date_first_available int64 Date first time the product was available
manufacturer str Manufacturer of the product
brand_name str Brand name
color str color
package_weight str Package weight
item_package_dimensions_l_x_w_x_h str Dimensions of the package item LxWxH
part_number str Part number
material str Material
best_sellers_rank str Best seller rank
size str Size
style str Style
brand str Brand
suggested_users str Suggested users
item_weight str Weight of the item
item_dimensions__lxwxh str Item dimensions LxWxH
department str Department
sport_type str Sport type