Learner Profiles

Sarah runs circulation services at a large public library system. She’s handy with ILS exports, but compiling monthly stats across dozens of branches still takes hours of tedious Excel copy-pasting. Learning Python loops and Pandas will help her aggregate those branch CSVs automatically so she can streamline her monthly reporting.

David is a community college assessment librarian who feels confident in spreadsheets, but has never written code. He’s currently stuck wrestling with years of messy gate counts and inconsistent vendor stats, making this lesson’s focus on JupyterLab and Pandas perfect for learning how to tidy up and plot his data.

Ling advises university faculty and students on data management, but doesn’t write code herself. Mastering Python basics like lists, functions, and built-in help will allow her to read her researchers’ scripts with confidence and run quick exploratory checks on repository datasets.

Mateo works with digital collection metadata and knows XML inside out, but spreadsheets are no longer cutting it for his huge batch cleanup jobs. Building a foundation in Python logic and functions will give him the exact leverage he needs for heavy data wrangling and future API integration.