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Library/ EDA/ Exploratory Data Analysis by Building (two projects in parallel)/ E03 · Build: Data Quality & Missing-Value Log

subtopic

Quantify missingness

10 min applied10 min research2 curated resources

Missing count and % per column, sorted; missing per row. Concepts: Missingness rates; row vs column view Project A: Zero NaN values — report it, but continue to the next step: missingness can hide inside categories. Project B: Several generation columns are entirely empty → drop; a few hours of load are missing; weather has occasional gaps.

Builds on: B14 · Build: Data Cleaning Clinic (messy customer data)

Notes, key code, what to skip and 2 curated resources are inside the platform.Join the waitlist and we'll build you a roadmap that includes this topic only if your goal needs it.

Quantify missingness · 1x1labs.ai