reporting-derived-metrics

wdm0006/python-skills

Compute and report statistics, scores and flags from samples that may be too small - or too heavy-tailed - to support them: undefined dispersion returned as 0.0 and tripping a minimum threshold, sentinel choice, threshold blocks gated on whether the value was measured, reports that narrate findings from absent data, nullability as a public API change, broad excepts that disguise a metric bug as a normal result, and cohort comparisons where one outlier makes the mean point the opposite way to the median

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