Who_Dunnit.xlsx – Teaching Python through Data Investigation
summary
Uses Python in Excel or Jupyter to load spreadsheets into pandas, indexes the science row of a walk-time matrix, filters period‑3 timetables, merges attendance and timetables with a pandas merge, adds simple string parsers like get_hour/get_minute for canteen timestamps, and applies successive boolean filters to narrow suspects — a small class example scales to hundreds and reduces to one named culprit Mia Kim, so the classroom mystery is solvable end to end.
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chapters (18)
- 0:00Introduction
- 1:04About the talk
- 2:27Teaching Python despite AI
- 5:19Python in Excel
- 8:06Python in Excel benefits
- 9:52Python in Excel use cases
- 11:16Missing snake mystery
- 13:03Solving mystery with data
- 14:05Loading walk time data
- 15:32Identifying nearby students
- 17:20Checking attendance
- 18:42Merging suspect data
- 20:07Time data and functions
- 21:13Canteen purchases alibi
- 22:16Extending mystery with data
- 23:38Python concepts through mystery
- 25:02Alternative tools for schools
- 25:24Summary and resources
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