Python Data Scraping Project – Winter Trends Tracker

Title: "Winter Trends Tracker: Data-Driven Insights"

Objective: Build a Python script to scrape product data from Amazon and Best Buy to identify trends and insights during the winter sale season. The project focuses on web scraping, data analysis, and visualization.

Features:

Scraping Requirements:

• Use BeautifulSoup and Requests (or Scrapy for advanced users) to scrape product details:

• Product Name, Price, Discount Percentage, and URL

• Target Categories: Laptops and headphones

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Data Analysis:

• Use Pandas to clean and organize the data

Perform analysis to:

• Identify top deals (highest discount percentage)

• Calculate average discounts per category

• Generate simple visualizations (e.g., bar charts) using Matplotlib or Seaborn

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Submission Requirements:

• Python script submitted via GitHub

• CSV file of scraped data (sample of at least 20 products)

• Screenshots of visualizations

• A short write-up (300-500 words) explaining the scraping process and insights gained