Workflow:
Data Collection:
- Develop web scraping tools to extract card game prices from TCG Player.
- Gather comprehensive data encompassing card details, store prices, and additional attributes.
Data Comparison and Analysis:
- Compare scraped prices against market rates to identify discrepancies and advantageous deals.
- Analyze price trends, fluctuations, and variations across stores and card types.
Optimization:
- Implement algorithms to identify optimal deals based on scraped data and market prices.
- Formulate strategies to recommend the best deals to users, considering factors like card condition, rarity, and price differences.
Visualization and Reporting:
- Visualize price variations, trends, and comparative analyses through charts, graphs, or dashboards.
- Generate reports showcasing the best deals and price differentials for user reference.
Insight: Utilizing web scraping techniques, this project aims to amass card game prices from diverse online stores, enabling a comprehensive comparison with market rates. Through analysis and optimization algorithms, the goal is to unearth the most favorable deals for users, factoring in card attributes and price differentials. Ultimately, this initiative seeks to empower users with actionable insights, allowing them to make informed purchasing decisions for card games.
Check full code on my GitHub Repository
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