Datasets:
metadata
annotations_creators:
- other
language_creators:
- other
language:
- en
license:
- unknown
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- text-classification
- image-classification
- feature-extraction
- image-segmentation
- image-to-image
- image-to-text
- object-detection
- summarization
- zero-shot-image-classification
pretty_name: Austria - Net-a-Porter - Product-level price list
tags:
- webscraping
- ecommerce
- Net
- fashion
- fashion product
- image
- fashion image
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: website_name
dtype: string
- name: competence_date
dtype: string
- name: country_code
dtype: string
- name: currency_code
dtype: string
- name: brand
dtype: string
- name: category1_code
dtype: string
- name: category2_code
dtype: string
- name: category3_code
dtype: string
- name: product_code
dtype: int64
- name: title
dtype: string
- name: itemurl
dtype: string
- name: imageurl
dtype: string
- name: full_price
dtype: float64
- name: price
dtype: float64
- name: full_price_eur
dtype: float64
- name: price_eur
dtype: float64
- name: flg_discount
dtype: int64
splits:
- name: train
num_bytes: 17632573
num_examples: 43237
download_size: 5526380
dataset_size: 17632573
Net-a-Porter web scraped data
About the website
The EMEA industry, particularly in Austria, is a dynamic and competitive marketplace. It is characterized by a rapidly growing e-commerce sector, driven by technological advancements and changing consumer behavior. A significant player in this space is Net-a-Porter, a leading global online luxury fashion retailer. The observed dataset provides detailed Ecommerce product-list page (PLP) data on Net-a-Porter in Austria. The PLP data can provide valuable insights into customer preferences, shopping behavior, and market trends. This data is crucial for businesses to remain competitive and adapt to the needs of the digital consumer in the modern Austrian e-commerce landscape.