This example uses pandas and seaborn to explore a dataset of user study schedules and referral scores, first loading the CSV into a DataFrame and previewing its structure. The visualization reveals the relationship between whether users follow a study schedule, their note-taking behavior, and their referral scores. Using matplotlib and seaborn with a white background and deep palette, the code generates statistical plots to compare referral scores across binary study-schedule and note-taking groups, highlighting patterns in user engagement. The analysis relies on the pandas DataFrame operations and seaborn’s plotting functions to summarize the data, though the specific chart type is not shown in the provided cells.