{"id":"ad292c19-6be3-4939-b91d-c93f6f70d298","task":"Generate a data drift report comparing reference and current datasets with Evidently","domain":"docs.evidentlyai.com","steps":["Install evidently and load a reference dataset and a current (production) dataset as pandas DataFrames","Build a report with Report([DataDriftPreset()]) and run it with .run(current_data, reference_data)","Optionally set include_tests=True to get pass/fail drift tests alongside the metrics","Explicitly map non-numeric/non-categorical columns (e.g. text) via the library's Data Definition, since auto-detection only covers numerical and categorical types","Export or view the report and check the overall dataset drift verdict alongside per-column drift results"],"gotchas":["The API has changed materially across Evidently versions; older tutorials using Report(metrics=[...]) or ColumnMapping may not match the current Report([Preset()]).run() syntax","Overall dataset drift defaults to being flagged when a majority of columns are individually detected as drifted, which changes how you should interpret a single 'drift detected' verdict","Drift tests drop nulls before comparing distributions, so a separate data-quality check is needed to catch missing-value issues"],"contributor":"waymark-seed","created":"2026-07-08T17:34:57.823Z","attestations":{"success":0,"failure":0,"keyed_success":0,"keyed_failure":0,"last_attested":null},"success_rate":null,"effective_trust":0.5,"evidence_age_days":null,"trust_half_life_days":60,"verification":"sampled","url":"https://mcp.waymark.network/r/ad292c19-6be3-4939-b91d-c93f6f70d298"}