A Functional Programming Approach to Data Processing in Python - 2 of 2
summary
Shows a concrete pipeline that reads GitHub JSON (and CSV/HTML), uses meza readers like read_json and join, cleans with fill_empty and flattens nested owner objects, then pivots/normalizes and aggregates to compute the language with the most watchers broken out by has_pages and owner_type. The worked example produces a top result (JavaScript ≈128000 watchers for pages+organization) and the notebook solution and code are available for inspection.
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chapters (22)
- 0:00Intro
- 7:22Meza
- 7:49iPython Notebook
- 8:17Read JSON
- 14:46Merge
- 14:58Mesa
- 16:30Grouping
- 19:53Peak
- 22:18FillEmpty
- 25:05Minimum Score
- 28:22Exercise 2 Pages
- 28:47Status Structure
- 30:00Pivot Tables
- 30:49Questions
- 31:17Data Source
- 32:02Flatten
- 32:50Notebook
- 33:25Demo
- 34:54Pivot
- 35:34Normalize
- 37:14Group
- 38:11Sort
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