Python web scraping project built to extract Amazon product data, track product information, and prepare structured data for analysis and reporting.
This project demonstrates how Python can collect product data from Amazon, structure the extracted information, and prepare it for tracking or analysis.
Extracted product details such as title, price, rating, or related product attributes.
Used Python logic to support repeatable product monitoring and data collection.
Prepared scraped data for review, CSV export, reporting, or future analysis.
Product information from ecommerce websites can change frequently. Manually checking product titles, prices, and details is repetitive, time consuming, and difficult to scale when tracking multiple products.
I created a Python web scraper that collects Amazon product information and prepares the extracted data for analysis. This workflow demonstrates how Python can automate product monitoring and reduce manual data collection work.
This project shows how Python can automate ecommerce data collection, support product monitoring, reduce manual research effort, and prepare product information for analysis or reporting.
Key automation and data extraction skills demonstrated in this project.
Used Python to extract information from web page elements and prepare the data for review.
Demonstrates how product information can be collected for tracking and analysis.
The notebook can be adapted for other scraping or data collection use cases.
The complete Python notebook and source code are available on GitHub.
I can help build Python web scraping workflows, API automation, SQL reports, Power BI dashboards, and reporting automation solutions.