Back to Projects

Web Scraping & Data Science

Individual Project

Individual Project (Data Science)

Web Scraping & Data Science

Individual Project (Data Science)

This data science project involved scraping and analyzing lineup data from major Belgian festivals including Tomorrowland, Rock Werchter, Pukkelpop, and Graspop Metal Meeting. The goal was to uncover trends and insights in festival performances over the years. Web scraping was executed using BeautifulSoup and Selenium to gather detailed festival lineup data. Applied comprehensive data cleaning, normalization, and handling of missing data to prepare the dataset for analysis. Conducted exploratory data analysis (EDA) to identify key trends, answering multiple analytical questions about artist appearances, festival continuity, and lineup evolution. Presented findings through an interactive Jupyter notebook clearly outlining the analytical process and insights.

Key Learnings:

  • Advanced web scraping techniques using BeautifulSoup and Selenium
  • Data normalization and cleaning using Regex and Python
  • Exploratory data analysis (EDA) and data visualization
  • Formulating analytical questions based on scraped data
  • Reporting insights effectively using Jupyter notebooks

Screenshots

Web Scraping & Data Science screenshot 1
Web Scraping & Data Science screenshot 2

Technologies Used:

PythonBeautifulSoupSeleniumPandasMatplotlibSeaborn

My Contribution

I performed the entire data collection process through web scraping, cleaned and normalized the data, formulated meaningful analytical questions, executed detailed exploratory data analysis, and prepared an insightful report to clearly communicate findings.