I contributed to my first open source project, which is a documentation to help tertiary students learn about Python modules/libraries they might use to aid their studies.

For example, I studied library and information science and can utilize Pandas. Pandas is a data analysis and manipulation library used to manage and analyze library and information science datasets, such as catalog data, user surveys, and access logs.

Pandas is crucial for anyone working in library and information science, providing powerful capabilities for handling and analyzing massive datasets. It excels at managing structured data, such as library catalogs, user surveys, and access logs, necessary for making educated decisions and understanding user behavior. Pandas facilitate data analysis with its clear syntax and extensive functions, which include data cleansing, transformation, and aggregation. Pandas is a robust and versatile platform that allows library and information professionals to extract valuable insights from their data, whether altering catalog data to better library services or analyzing user surveys to improve user experience.

Imagine you had a large toy box loaded with many types of toys. Some are cars, while others are toys or blocks. Now, you want to find all the red automobiles without searching the entire box. Pandas is like a magical friend who helps you sort and locate your toys quickly. So, if you say, "I want to see all the red cars," Pandas will find them for you in no time. It's like playing a game where Pandas help you arrange and find your toys, allowing you to have more fun while spending less time searching.