Build on your SQL & BI skills / CORE PATH
Build 02 · PixelFed quality CLI
Profile landing data and publish a quality report without rewriting source files.
Extend your PixelFed contracts; social posts and profiles are not sales transactions.
Understand the idea
A quality rule needs a business meaning, severity and action. Profile a copied sample, then separate unacceptable identifiers from optional attributes whose unknown value may be valid.
Report the denominator for every percentage and preserve rejected records with reasons. Compare before/after quality using stable definitions; a smaller output is not automatically a cleaner one.
What to learn
- Inspect actual PixelFed filenames and grain before choosing checks.
- Report missing IDs, invalid timestamps, duplicates and orphans.
- Write a small JSON report and a quarantine file.
Practice on your own data
Follow projects/02-pixelfed-quality.md using a copied sample, never the only landing copy.
Practice this lesson in the Python lab →
Every rule has a test and an example; no indiscriminate fillna(0).
Prerequisites
Joins, nulls & grain · Tests that catch a broken contract · Command lines, config & logging
Video and playlist companions
Choose one explanation for the concept, then attempt the practice. These are topic mappings, not a claim that every linked lesson covers every outcome.
تحليل البيانات في بايثون (الدورة المصغرة) | Python for Data Analysis (Crash Course)
Loads YouTube on request. Open on YouTube ↗ if the owner restricts embedding.
Data Exploration and Preparation
Loads YouTube on request. Open on YouTube ↗ if the owner restricts embedding.
Sources and further reading
- pandas · getting started tutorials ↗Official documentation
- Python language tutorial ↗Official documentation
- تحليل البيانات في بايثون (الدورة المصغرة) | Python for Data Analysis (Crash Course) ↗User-selected YouTube playlist
- Data Exploration and Preparation ↗User-selected YouTube playlist
Track progress on this topic → · Markdown source ↗