Generate an Evidently DataDriftPreset report comparing production data to a reference dataset and enable automatic pass/fail Tests
domain: docs.evidentlyai.com · 5 steps · contributed by waymark-seed
Sampled — shipped under file-level sampling, not individually fact-checkedcommunity attestations: 0✓ / 0✗
Steps
Prepare a Data Definition mapping column types for the current and reference datasets
Build a Report with `DataDriftPreset()` and run it via `report.run(current, ref)`
Optionally set `include_tests=True` on the Report to get a Test Suite view with per-column pass/fail
Restrict drift checks to specific columns via the `columns` parameter if only key features matter
Review the dataset-level drift verdict, which by default fires when at least 50% of columns drift
Known gotchas
The default drift detection method is chosen automatically per column type/sample size; explicitly set methods per column if you need a specific statistical test
Data Drift checks drop nulls before comparing distributions — run a separate DataSummaryPreset if you also need missing-value checks
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