QuantEcon / QuantEcon/lecture-python.myst

[ak2] Editorial Suggestions (carried over from intro repo #491)

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TeX
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123
Forks
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Avg merge
3d 10h
Merged PRs (30d)
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Description

This issue bundles the remaining unchecked editorial items from QuantEcon/lecture-python-intro#491. The ak2 lecture was removed from lecture-python-intro in QuantEcon/lecture-python-intro#549 and now lives here, so the open suggestions are being re-filed against this repo for triage.

The section/equation numbers below reference the version of the lecture as it stood when the original issue was filed; reviewers should map them to the current section structure here.

Content

  • Starting from section 31.10.4, reconsider plotting a graph for every single variable — keep graphs only for those that are discussed in the surrounding text. The graphs are dense and hard to read, and the prose doesn't clearly explain the conclusion being drawn from each figure. Tighten the link between figures and the explanation below them.

Code

  • For the code block in section 30.10.3, remove the class wrapper and refactor to plain functions.
  • Convert the plotting code to the object-oriented matplotlib API. Search for uses of plt.<...> and replace with fig, ax = plt.subplots() / ax.<...> style. Use the default figure size, make the plotting code stand out clearly, and let matplotlib pick colours rather than hard-coding them.

Context

Originally filed by @Jiarui-ZH at QuantEcon/lecture-python-intro#491 with comments from @pgrosser1. Items already done in the original issue (rephrasing around equations 31.3 and 31.8, replacing njit usage) were addressed before the lecture moved, so they aren't repeated here. The related sub-issue QuantEcon/lecture-python-intro#507 is closed.

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the current ak2 lecture and map the old section references, especially sections 30.10.3 and 31.10.4, to its present structure. Review the surrounding prose and plots, search the lecture for plt.<...> calls and the class wrapper, then update the figures and code so the rendered lecture clearly connects each retained graph to its explanation.

Written by the indexing model from the issue text.

Assessment

Tech stack
matplotlib, python
Domain
data-visualization, documentation
Issue type
Documentation
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
52/100

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