📊 DataMiner Pro

AI-Powered Web Scraping, Data Cleaning & Excel Report Generation Platform

🚀 Modern AI-Style Analytics & Scraping Dashboard

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✨ Features

🔍 Smart Web Scraping

• Extract product/listing data from websites
• Supports static and dynamic pages
• Multi-page scraping support
• Auto scraping mode detection

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🧹 Intelligent Data Cleaning

• Remove duplicates
• Handle missing values
• Normalize prices and ratings
• Clean inconsistent formatting

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📊 Analytics Dashboard

• Product statistics
• Average pricing insights
• Rating analysis
• Category breakdown
• Duplicate tracking

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📁 Export System

• Export CSV reports
• Export professional Excel reports
• Styled spreadsheets
• Auto formatted columns

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⚡ Advanced Features

• Selenium support for JavaScript websites
• Scheduled scraping support
• Progress tracking
• Live scraping logs
• AI-style insights
• Responsive dashboard UI

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🧠 Workflow

Input Website URL
        ↓
Fetch HTML Content
        ↓
Parse Product Cards
        ↓
Extract Data
        ↓
Clean & Normalize
        ↓
Generate Analytics
        ↓
Export Excel/CSV Reports

Architecture

flowchart TD
    A["User enters URL"] --> B["Scraper: requests or Selenium"]
    B --> C["Parser: product/listing extraction"]
    C --> D["Cleaner: Pandas validation and normalization"]
    D --> E["Exporter: CSV and Excel"]
    D --> F["Dashboard: stats and charts"]
    G["Scheduler"] --> B

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🏗️ Project Structure

dataminer-pro/
├── main.py
├── requirements.txt
├── README.md
├── .env
├── src/
│   ├── scraper.py
│   ├── parser.py
│   ├── cleaner.py
│   ├── exporter.py
│   ├── scheduler.py
│   ├── config.py
│   ├── logger.py
│   └── utils.py
├── output/
│   ├── reports/
│   └── csv/
├── logs/
├── screenshots/
└── assets/
    └── styles.css

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🛠️ Tech Stack

Technology	Purpose
Python	Core Backend
BeautifulSoup	HTML Parsing
Selenium	Dynamic Scraping
Pandas	Data Cleaning
Openpyxl	Excel Reports
Streamlit	Dashboard UI
APScheduler	Automation

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🚀 Installation

1️⃣ Clone Repository

git clone https://github.com/your-username/dataminer-pro.git
cd dataminer-pro

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2️⃣ Create Virtual Environment

python -m venv venv

Windows

venv\Scripts\activate

Mac/Linux

source venv/bin/activate

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3️⃣ Install Dependencies

pip install -r requirements.txt

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▶️ Run Application

streamlit run main.py

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🌐 Example Websites

Static Website

https://books.toscrape.com/

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Dynamic Website

Use Selenium mode for:

• Infinite scroll
• JavaScript-rendered pages
• Dynamic product loading

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📊 Dashboard Features

Analytics Cards

• Total Products
• Average Price
• Top Category
• Duplicate Count
• Average Rating

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Interactive Table

• Product preview
• Filtering
• Sorting
• Pagination

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Export Options

• CSV Export
• Excel Export
• Styled Reports

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⚙️ Scraping Modes

Mode	Description
Auto	Detect scraping strategy automatically
BeautifulSoup	Fast static scraping
Selenium	Dynamic JavaScript scraping

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📈 Planned Improvements

• 🤖 AI-generated data insights
• 📧 Automated email reports
• 🕒 Scheduled scraping jobs
• 🌍 Proxy rotation
• 🔒 CAPTCHA handling
• 📊 Interactive visual analytics
• ☁️ Cloud deployment support

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📸 Highlights

This project demonstrates:

✅ Web Scraping
✅ Automation Engineering
✅ Data Cleaning Pipelines
✅ Analytics Dashboard Design
✅ Excel Report Generation
✅ Selenium Automation
✅ BeautifulSoup Parsing
✅ SaaS-style UI Development

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🧪 Test Dataset

Recommended demo site:

https://books.toscrape.com/

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📦 Requirements

beautifulsoup4
requests
selenium
pandas
openpyxl
streamlit
lxml
webdriver-manager
apscheduler

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👩‍💻 Author

Amna Chaudhary

AI & Automation Developer

• Generative AI
• Agentic AI Systems
• Automation Workflows
• AI SaaS Applications

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⭐ Support

If you found this project useful:

⭐ Star the repository
🍴 Fork the project
📢 Share with others

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📄 License

This project is licensed under the MIT License.

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🔥 DataMiner Pro

Turning raw web data into actionable insights.