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Description
Not sure if this fits rather into an existing "redesign" epic.
Based on my limited experience with python, and even more limited exposure to the course, I got the feeling the scope of the course might be too broad. I can think of a split:
[the numbers in brackets correspond to the current chapters]
Basic Intermediate / Data analysis: What anyone might need to do some data analysis from a local data file on a single script
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[1] Basics Recap -- Skip? We have to make a cut somewhere, and assume that participants come with a minimal background.
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[3] Numpy and Matplotlib
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[7] Pandas
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Topics included in the Python introduction course, but not actually covered in our introductory course? (not sure what currently gets covered)
- [5]. Defensive Programming?
- Functions and loops?
- Command Line programs?
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Others (things we currently assume participants will just pick up along the way)
- Best practices: how to write a clean script (separating data, parameters, and methods; documentation, etc.)
- Installing packages (
pip)
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[6] Units and Quantities -- leave it as an optional here, because it ties with Numpy?
Advanced Intermediate:
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[2] Dictionaries and JSON data
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[4] Package Management (environments)
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Others, e.g.
- Other data structures (sets, tuples, dataclasses?)
- List comprehensions
- Functions with
*args, and**kwargs, be aware that some objects are passed by reference - Relative imports? (writing a simple package)
- Testing
- ...