Analyzing survey data about bathroom stall doors from the DSGN1 course at UCSD

This was part of a group project for my DSGN1 course at UCSD where we wanted to understand how people actually experience bathroom stall doors - whether they're intuitive, offer enough privacy, and are easy to use. The goal was to analyze bathroom stall doors using design principles like signifiers, affordances, gulf of execution, gulf of evaluation, feedback, mental models, and mapping. But to really understand people's opinions and identify the deficits in these design principles, we needed to analyze the survey text and create visualizations so the findings could be easily understood and applied. I handled all the data processing and analysis side, building this comprehensive pipeline that could handle messy survey responses and extract meaningful insights. The most interesting part was developing the regex patterns to detect door swing preferences and sentiment - seeing how people actually feel about these everyday design elements was really eye-opening. To see the full report with all the visualizations and detailed findings, just message me. You can also check out the code and see the raw survey data for yourself.