This repository demonstrates how to collect data from the web using scraping techniques and turn it into meaningful visual insights through data visualization. It combines web scraping with data cleaning, analysis, and interactive visualizations to help better understand scraped information.
🔍 What's Inside
🕸️ Web Scraping Scripts – Python scripts using BeautifulSoup, requests, and/or Selenium
📄 Scraped Datasets – Exported data in CSV/JSON formats
🧹 Data Cleaning – Preprocessing scraped data for analysis
📊 Visualizations – Charts and graphs using Matplotlib, Seaborn, Plotly, etc.
📓 Jupyter Notebooks – Step-by-step analysis and visualization process
🛠️ Technologies Used
Python (BeautifulSoup, Requests, Selenium)
Pandas, NumPy
Matplotlib, Seaborn, Plotly
Jupyter Notebook
🚀 How to Use
Clone the repo git clone https://github.com/your-username/data-visualization-web-scraping.git
Install dependencies pip install -r requirements.txt
Run the scraping script to collect data
Explore the notebooks to visualize and analyze the data
📚 Ideal For
Beginners learning web scraping and visualization
Analysts looking to extract and explore web data
Data enthusiasts working on real-world datasets