Python Final Project — Web Scraping & Dashboard (Dash)

Project Overview

This project is an end-to-end data pipeline that involves:

• Scraping historical baseball data using Selenium
• Saving the raw data as CSV files
• Importing data into a SQLite database
• Querying the database via the command line
• Building an interactive dashboard using Dash

Project Structure

python_final_project/
├── app/                    # Dash visualization app
│   └── dashboard.py
├── cli/                    # Command-line interface
│   └── query_mlb.py
├── data/                   # CSV data and database
│   ├── american_league_pitcher_stats_1901_2024.csv
│   ├── american_league_stats_1901_2024.csv
│   ├── mlb_events.csv
│   └── mlb_stats.db
├── scraper/                # Scripts for data scraping and processing
│   ├── import_to_sqlite.py
│   ├── list_events.py
│   └── scraper.py
├── screenshots/
│   ├── charts.png
│   └── table.png
├── venv/                   # Virtual environment (gitignored)
├── requirements.txt        # List of dependencies
├── README.md               # Project overview and instructions
└── .gitignore              # Git ignore rules

How to Run the Project

1. Install dependencies

pip install -r requirements.txt

2. Run the scraper

python scraper/scraper.py

3. Import data into SQLite

python scraper/import_to_sqlite.py

4. Launch the dashboard

python app/dashboard.py

Technologies Used

• Python
• Selenium – for web scraping
• Pandas – for data cleaning and transformation
• SQLite – as the database engine
• Dash – for dashboard visualization

Data Source

Data is scraped from the Major League Baseball History website, which includes player stats, historical events, and yearly achievements.

Screenshots

Author

Created by Alena Danilchenko. This project is part of the CTD Python course — Lesson 14 Final Project.

License

This project is for educational use only.