Love Island Data Visualizations

Project Description 

This project consists of web scraping the Love Island Fandom webpage via each individual Love Island UK’s contestant page. After web scraping the information, I transformed the birthdate data to determine each contestant’s Zodiac sign. I then compiled all of the data into one CSV which I utilized to create data visualizations.

Methods

Utilizing python programming language I created two data documents that were web scraped from the Love Island UK fan webpages. One csv contains all of the URLs that were web scraped for the project and the other contains all of the data compiled for this project.

In order to create the csv’s I wrote code to web scrape, convert long form dates to DD-MM-YYYY, from there I converted the date of the zodiac sign of each contestant. I modelled some of my code from GitHub user Crusat's Python Zodiac Code. After this I used code to clean up the data and create simple data visualizations. 

My Role — Individual

Learning Outcome Achieved – Technology

Rationale

This project demonstrates mastery of digital tools and technology by employing web scraping, data transformation, and visualization techniques to analyze Love Island UK contestant data. It effectively utilizes Python to automate data collection, clean and process information, and generate meaningful insights, aligning with the learning outcome of applying technical skills to investigate and present information.

The project showcases an advanced understanding of scripting by developing a Python program to scrape contestant data from the Love Island fandom website. The script extracts birthdates, transforms them into a standardized format, and calculates zodiac signs before compiling the cleaned data into a structured CSV. This process reflects the ability to troubleshoot and refine scripts to handle inconsistencies in web data.

Additionally, this work demonstrates effective use of digital tools for data organization, access, retrieval, and visualization. By leveraging existing Python resources, such as GitHub user Crusat’s Zodiac Code, the project also illustrates an ability to adapt and integrate external code to enhance functionality. This work provides evidence of technical proficiency in web scraping, data processing, and visualization—key competencies in the LIS field. It not only applies technology meaningfully but also engages with contemporary trends in data analysis and digital information management, positioning me as a capable user of computational tools for information organization and research.