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Implementation:Evidentlyai Evidently DriftedColumnsCount MissingValueCount

From Leeroopedia
Knowledge Sources
Domains ML_Monitoring, Data_Quality
Last Updated 2026-02-14 12:00 GMT

Overview

Concrete metric classes for dataset-level drift counting and missing value detection provided by the Evidently library.

Description

  • DriftedColumnsCount: Tests all specified columns for drift and returns the count and share of drifted columns
  • MissingValueCount: Counts missing (null/NaN) values in a specific column, returning count and share

Usage

Include in Report metrics lists for drift monitoring workflows.

Code Reference

Source Location

  • Repository: evidently
  • File: src/evidently/metrics/column_statistics.py
  • Lines: L492-524 (MissingValueCount), L745-783 (DriftedColumnsCount via dataset_statistics re-export)

Signature

class DriftedColumnsCount(Metric):
    columns: Optional[List[str]] = None
    drift_share: float = 0.5
    method: Optional[str] = None

class MissingValueCount(ColumnMetric, CountMetric):
    # column: str (inherited from ColumnMetric)

Import

from evidently.metrics import MissingValueCount
from evidently.metrics.dataset_statistics import DriftedColumnsCount

I/O Contract

Inputs

Metric Key Parameters Description
DriftedColumnsCount columns: Optional[List[str]], drift_share: float, method: Optional[str] Columns to check, share threshold, drift method
MissingValueCount column: str Column to check for missing values

Outputs

Metric Returns Description
DriftedColumnsCount (count: int, share: float) Number and share of drifted columns
MissingValueCount (count: int, share: float) Number and share of missing values

Usage Examples

from evidently import Report
from evidently.metrics import ValueDrift, MissingValueCount
from evidently.metrics.dataset_statistics import DriftedColumnsCount

report = Report([
    ValueDrift(column="age"),
    ValueDrift(column="salary"),
    ValueDrift(column="department"),
    DriftedColumnsCount(),  # Summary: how many columns drifted
    MissingValueCount(column="age"),
    MissingValueCount(column="salary"),
])

snapshot = report.run(current_dataset, reference_dataset)

Related Pages

Implements Principle

Uses Heuristic

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