A comprehensive set of Jupyter notebooks for scraping data from Amazon. Extract product details, prices, ratings, and table data efficiently. Perfect for data analysis, research, and e-commerce insights. Easy setup and use with detailed documentation and examples.
This project includes Jupyter notebooks designed to scrape data from Amazon's website. The goal is to extract relevant information from product pages and tables for further analysis.
- Amazon Web Scraper Project.ipynb: A comprehensive notebook for scraping product details from Amazon.
- Scraping a Table from a Website (FINAL).ipynb: A final version of a notebook that focuses on scraping table data from a website.
- Extract product names, prices, ratings, and other details from Amazon product pages.
- Scrape table data efficiently for structured information.
- Handle pagination and dynamic content loading.
- Python 3.x
- Jupyter Notebook
- BeautifulSoup
- Requests
- Pandas
- Selenium (if applicable)
- Clone the repository:
git clone https://github.com/yourusername/Amazon-Web-Scraper.git
- Install the required packages:
pip install -r requirements.txt
- Open the Jupyter notebooks:
jupyter notebook
- Open
Amazon Web Scraper Project.ipynb
orScraping a Table from a Website (FINAL).ipynb
. - Run the cells to execute the scraping scripts.
- Modify the parameters as needed for different product searches or table data.
- Fork the repository.
- Create a new branch (
git checkout -b feature-branch
). - Commit your changes (
git commit -am 'Add new feature'
). - Push to the branch (
git push origin feature-branch
). - Create a new Pull Request.
This project is licensed under the MIT License.
pycache/ .ipynb_checkpoints/ .env *.pyc *.pyo *.pyd
List of required packages beautifulsoup4 requests pandas selenium # If your scripts use Selenium
Amazon-Web-Scraper/ │ ├── Amazon Web Scraper Project.ipynb ├── Scraping a Table from a Website (FINAL).ipynb ├── README.md ├── requirements.txt