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---
dataset_info:
features:
- name: title
dtype: string
- name: average_rating
dtype: string
- name: rating_number
dtype: string
- name: features
dtype: string
- name: description
dtype: string
- name: price
dtype: string
- name: images
dtype: string
- name: videos
dtype: string
- name: store
dtype: string
- name: categories
dtype: string
- name: parent_asin
dtype: string
- name: date_first_available
dtype: timestamp[s]
- name: department
dtype: string
- name: manufacturer
dtype: string
- name: item_model_number
dtype: string
- name: package_dimensions
dtype: string
- name: country_of_origin
dtype: string
- name: is_discontinued_by_manufacturer
dtype: string
- name: product_dimensions
dtype: string
- name: item_weight
dtype: string
- name: brand
dtype: string
- name: color
dtype: string
- name: material
dtype: string
- name: age_range_(description)
dtype: string
- name: style
dtype: string
- name: size
dtype: string
- name: closure_type
dtype: string
splits:
- name: train
num_bytes: 110486655
num_examples: 43070
download_size: 46484678
dataset_size: 110486655
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Amazon Fashion 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 Amazon Fashion meta dataset.
### Dataset Description
The Amazon Fashion 2023 dataset contains information on fashion products from Amazon, including titles, ratings, descriptions, prices, and categories. Each entry includes product-specific attributes like color, size, brand, and materials, along with identifiers like ASIN and department. It also holds metadata such as release dates, package dimensions, and origin.
The table below represents the original structure of the dataset.
<table border="1" cellpadding="5" cellspacing="0">
<tr>
<th>Field</th>
<th>Type</th>
<th>Explanation</th>
</tr>
<tr>
<td>main_category</td>
<td>str</td>
<td>Main category (i.e., domain) of the product.</td>
</tr>
<tr>
<td>title</td>
<td>str</td>
<td>Name of the product.</td>
</tr>
<tr>
<td>average_rating</td>
<td>float</td>
<td>Rating of the product shown on the product page.</td>
</tr>
<tr>
<td>rating_number</td>
<td>int</td>
<td>Number of ratings in the product.</td>
</tr>
<tr>
<td>features</td>
<td>list</td>
<td>Bullet-point format features of the product.</td>
</tr>
<tr>
<td>description</td>
<td>list</td>
<td>Description of the product.</td>
</tr>
<tr>
<td>price</td>
<td>float</td>
<td>Price in US dollars (at time of crawling).</td>
</tr>
<tr>
<td>images</td>
<td>list</td>
<td>Images of the product. Each image has different sizes (thumb, large, hi_res). The “variant” field shows the position of image.</td>
</tr>
<tr>
<td>videos</td>
<td>list</td>
<td>Videos of the product including title and url.</td>
</tr>
<tr>
<td>store</td>
<td>str</td>
<td>Store name of the product.</td>
</tr>
<tr>
<td>categories</td>
<td>list</td>
<td>Hierarchical categories of the product.</td>
</tr>
<tr>
<td>details</td>
<td>dict</td>
<td>Product details, including materials, brand, sizes, etc.</td>
</tr>
<tr>
<td>parent_asin</td>
<td>str</td>
<td>Parent ID of the product.</td>
</tr>
<tr>
<td>bought_together</td>
<td>list</td>
<td>Recommended bundles from the websites.</td>
</tr>
</table>
### Modifications Made
<ul>
<li>Products without a description, title, images or details were removed.</li>
<li>Lists in features and description are transformed into strings concatinated with a newline</li>
<li>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.</li>
<li>Products with date first available before the year 2015 are dropped.</li>
<li>Products with is_discontinued_by_manufacturer set to 'true' or 'yes' are dropped.</li>
<li>Column bought_together is dropped due to missing values.</li>
</ul>
### Dataset Size
<ul>
<li>Total entries: 43 070</li>
<li>Total columns: 27</li>
</ul>
### Final structure
<table border="1" cellpadding="5" cellspacing="0">
<tr>
<th>Field</th>
<th>Type</th>
<th>Explanation</th>
</tr>
<tr>
<td>title</td>
<td>str</td>
<td>Name of the product.</td>
</tr>
<tr>
<td>average_rating</td>
<td>float</td>
<td>Rating of the product shown on the product page.</td>
</tr>
<tr>
<td>rating_number</td>
<td>int</td>
<td>Number of ratings in the product.</td>
</tr>
<tr>
<td>features</td>
<td>list</td>
<td>Bullet-point format features of the product.</td>
</tr>
<tr>
<td>description</td>
<td>list</td>
<td>Description of the product.</td>
</tr>
<tr>
<td>price</td>
<td>float</td>
<td>Price in US dollars (at time of crawling).</td>
</tr>
<tr>
<td>images</td>
<td>list</td>
<td>Images of the product. Each image has different sizes (thumb, large, hi_res). The “variant” field shows the position of image.</td>
</tr>
<tr>
<td>videos</td>
<td>list</td>
<td>Videos of the product including title and url.</td>
</tr>
<tr>
<td>store</td>
<td>str</td>
<td>Store name of the product.</td>
</tr>
<tr>
<td>categories</td>
<td>list[str]</td>
<td>Subcategories of the product.</td>
</tr>
<tr>
<td>parent_asin</td>
<td>str</td>
<td>Parent ID of the product.</td>
</tr>
<tr>
<td>date_first_available</td>
<td>timestamp</td>
<td>First date when the product was available.</td>
</tr>
<tr>
<td>department</td>
<td>string</td>
<td>Department of the product. (E.g. womens, mens)</td>
</tr>
<tr>
<td>country_of_origin</td>
<td>string</td>
<td>Name of the country of origin</td>
</tr>
<tr>
<td>item_weight</td>
<td>string</td>
<td>Weight of the product in ounces or pounds.</td>
</tr>
<tr>
<td>brand</td>
<td>str</td>
<td>Brand name associated with the product.</td>
</tr>
<tr>
<td>manufacturer</td>
<td>str</td>
<td>Name of the company or manufacturer responsible for producing the product.</td>
</tr>
<tr>
<td>product_dimension</td>
<td>str</td>
<td>Dimensions of the product, typically including length, width, and height.</td>
</tr>
<tr>
<td>color</td>
<td>str</td>
<td>Primary color or color variants of the product.</td>
</tr>
<tr>
<td>material</td>
<td>str</td>
<td>Main materials used in the product’s construction.</td>
</tr>
<tr>
<td>is_discontinued_by_manufacturer</td>
<td>str</td>
<td>Indicates whether the product has been discontinued by the manufacturer.</td>
</tr>
<tr>
<td>item_model_number</td>
<td>str</td>
<td>Model number of the product as assigned by the manufacturer.</td>
</tr>
<tr>
<td>age_range_(description)</td>
<td>str</td>
<td>Recommended age range for the product, often used for toys or children’s products.</td>
</tr>
<tr>
<td>style</td>
<td>str</td>
<td>Style or design</td>
</tr>
<tr>
<td>size</td>
<td>str</td>
<td>Size of product</td>
</tr>
<tr>
<td>closure_type</td>
<td>str</td>
<td>Closure type (E.g. zipper, button)</td>
</tr>
</table>
### Usage
## Download the dataset
```ruby
dataset = load_dataset("smartcat/Amazon_Fashion_2023", split="train")
```
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