Dataset Documentation

  1. Dataset Overview:
  • The dataset contains information about products available on the online store.
  • The dataset provides details such as product URLs, SKUs, names, prices, categories, and availability.
  • The data is collected from the Hoeffner website and is updated regularly.

    2. Introduction:
  • The dataset is valuable for businesses operating in the e-commerce industry.
  • It allows businesses to analyze and understand the product offerings, prices, and availability on the online store.
  • The dataset enables businesses to gain insights into market trends, competitor analysis, and pricing strategies.

    3. Dataset Structure:
  • Product URL: The URL of the product on the website
  • Product SKU: The unique identifier for the product
  • Product Name: The name or title of the product
  • Product Price: The price of the product
  • Top Category: The top-level category to which the product belongs
  • Mid Category: The middle-level category to which the product belongs
  • Bot Category: The bottom-level category to which the product belongs
  • Product Availability: The availability status of the product (e.g., in stock, out of stock)

    4. Data Dictionary:
  • Product URL: String
  • Product SKU: String
  • Product Name: String
  • Product Price: Numeric (decimal or integer)
  • Top Category: String
  • Mid Category: String
  • Bot Category: String
  • Product Availability: String

    5. Dataset Documentation Articles:
  • No specific documentation articles are available for this dataset at the moment.

    6. Data Processing and Preparation:
  • The dataset is collected using web scraping techniques from the website.
  • Data cleaning and transformation may be performed to ensure data accuracy and consistency.

    7. Data Usage Guidelines:
  • The dataset is intended for analysis and research purposes.
  • Respect the terms of use and policies of the website.
  • Ensure compliance with applicable laws and regulations regarding data usage and privacy.

    8. Example Use Cases:
  • Analyzing product pricing trends and competitiveness
  • Monitoring product availability and stock levels
  • Conducting market research and competitor analysis
  • Generating insights for pricing strategies and assortment planning

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