Principle:Evidentlyai Evidently Column Statistics Metrics
| Knowledge Sources | |
|---|---|
| Domains | Data_Quality, Statistics, ML_Monitoring |
| Last Updated | 2026-02-14 12:00 GMT |
Overview
A collection of column-level statistical metrics for measuring central tendency, distribution shape, and category frequencies.
Description
Column Statistics Metrics provide fine-grained statistical measurements on individual columns:
- MeanValue: Arithmetic mean of a numerical column
- CategoryCount: Count occurrences of specific category values
- InRangeValueCount: Count values within a specified numerical range
- MissingValueCount: Count null/NaN values
These metrics are composable building blocks used both directly in Reports and as sub-components of presets. They enable precise monitoring of data quality properties like value distributions, missing data rates, and category frequencies.
Usage
Use when you need fine-grained column-level statistics beyond what presets provide. Include in Report metrics lists alongside or instead of presets.
Theoretical Basis
Column statistics implement standard descriptive statistics:
# Pseudocode
mean_value = sum(column) / len(column)
in_range_count = count(left <= x <= right for x in column)
category_count = count(x == target for x in column)
missing_count = count(isnan(x) for x in column)
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