UBC-MDS / UBC-MDS/programming-in-python-for-data-science

Comments on the syllabus

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Description

Comments on this document:

  • I would move apply and applymap later. It's a more advanced concept I think. Also, a lot of times you can just do things like df['new'] = df['old'] ** 2 (or whatever)
  • For the missing values (and one-hot encoding), there's the pandas way and the scikit-learn way. We should decide which one we're doing. If the latter, I guess we don't need to teach the pandas way?
  • Do we want/need regular expressions?
  • Module 6 looks too full to me. Functions are easily their own module IMO. I might move a bunch of it to Module 8.
  • Do we want/need broadcasting? For module 7, this might be their first time thinking about array shapes and dimensions.

Thanks @hfboyce !

cc @ttimbers

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Research direction

Start with docs/syllabus-learning-outcomes.md and review the comments about apply, applymap, missing values, one-hot encoding, regular expressions, functions, and broadcasting. Done means reaching and documenting clear decisions about the module placement and topics to teach.

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Assessment

Tech stack
numpy, pandas, python, scikit-learn
Domain
documentation
Issue type
Documentation
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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