The visualization tracks the author’s computer usage over time, comparing activity before and during their Hacker School batch. It reveals a clear shift toward coding-focused applications and increased keyboard input during the program. The notebook loads JSON time-tracking data from a Python script, then aggregates per-timestamp records of active windows, key presses, and mouse movement. Using Python’s `json` module and `defaultdict`, it processes the raw logs to compute daily summaries, which are plotted to show the “Hacker School Effect” as a rise in terminal and editor usage alongside a dip in browser time.