Web scraping project aritza-compressed
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The document details a student project presentation on a web crawler analysis of Aritzia, a publicly traded fashion brand. Key findings include insights on pricing trends, sales patterns, and stock changes related to promotional discounts. Challenges faced during the project involved data management and visualization using Python tools.
Web scraping project aritza-compressed
- 1. Data Science with Python Student Project Presentation WeCloudData @WeCloudData @WeCloudData tordatascience weclouddata WeCloudData tordatascience
- 2. Web Crawler Project - Aritzia By Shan Gao (WeCloudData)
- 3. Content Motivation Data Interesting Findings Conclusion Challenges
- 4. Info & Motivation ´ Type : Public ´ Traded as : TSX: ATZ ´ Industry : Fashion ´ Founded : 1984 ´ Founder : Brian Hill ´ Headquarters : Vancouver, British Columbia, Canada ´ Products : Clothing
- 5. Website
- 6. Dataframe ´ Total data : 856,452 ´ Date range : 2019-06-08 21:53:50 ~ 2019-06-20 13:57:19 ´ File numbers : 30
- 7. crawler.py
- 8. Interesting Findings ´ Categories & Brand ´ Price Distribution ´ Top 20 Colors ´ Weekdays Vs Weekend - Avg Stock ´ On Sale event - Discount% ´ Price Change Vs Stock Correlation
- 10. Brand Distribution Vs. Brand Average Price
- 11. Top 20 Colors
- 12. Weekdays Vs Weekend - Avg Stock
- 13. SALE !
- 14. Discount % of Each Brand
- 15. Top 10 products – stock change
- 16. Conclusion ´ Business casual clothes prices are higher than others ´ More transactions/purchases happens in weekends ´ Sale event – good deal for famous brands ´ Promotion influences stock change
- 17. Challenges ´ Save data as Tree structure (.json) ´ Load data ´ Move root node properties to children node ´ Data analyzing using Pandas ´ Visualization - Plotly (multi-chart types)
- 18. Next Step ´ Detailed size distribution of brands / products ´ Influences of the strength of discount ´ Stock refill timing ´ Long term data analyzing (winter vs. summer)