Expand Data Analysis Hard track content: more depth, examples, code - #64
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abderrahim-lectures merged 1 commit intoJul 21, 2026
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Substantially expands all 5 weeks with more explanation, worked examples, and code snippets: - Week 6: value_counts(normalize=True), reading skew from mean vs. median, IQR-based outlier detection, common pitfalls. - Week 7: bin-count sensitivity (with a side-by-side comparison), common pitfalls. - Week 8: correlation-strength rules of thumb, hue for a third variable on scatter plots, pd.crosstab for two categorical columns, common pitfalls. - Week 9: row+col faceting, colorblind-safe palette selection, plt.savefig for exporting charts, common pitfalls. - Week 10: a full report-structure recap table mapping every technique from Weeks 6-9 onto a section of the deliverable, plus a second worked example (a multivariate storytelling chart), common pitfalls. Each week also gains a "Common Pitfalls" section, additional challenges, socratic questions, and quiz questions. This completes the full course content expansion -- all 20 weeks, both sections, both tracks, now substantially more detailed than the original content pass. Closes #63
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July 21, 2026 11:03
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Summary
Substantially expands all 5 weeks of the Data Analysis Hard (EDA) track with more explanation, worked examples, code snippets, and a "Common Pitfalls" section per week. This completes the full course content expansion — all 20 weeks, both sections, both tracks. See commit message for the full per-week breakdown.
Closes #63
Test plan
npm run buildsucceeds for all locales