{"uid":"cap_LtwwmqKTEdcS2RvLlpc1k","slug":"feature-availability-exact-row-deduplication-keyed-dataset-comparison-fd0f3c05","name":"Feature Availability: Exact Row Deduplication + Keyed Dataset Comparison","description":"Feature availability — Exact row deduplication + Keyed dataset comparison: Exact row deduplication + Keyed dataset comparison for supplied feature availability records (populated_features, expected_features). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-053?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","populated_features","expected_features"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"expected_features":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"populated_features":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_features":1,"populated_features":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_features":2,"populated_features":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_features":3,"populated_features":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_features":4,"populated_features":30}],"maxItems":200,"minItems":1},"other":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","populated_features","expected_features"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"expected_features":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"populated_features":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_features":1,"populated_features":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_features":2,"populated_features":21},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_features":3,"populated_features":17},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_features":4,"populated_features":33}],"maxItems":200,"minItems":0}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_rgVn13rD19_4wmgbzLUdc","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Performs exact row deduplication and keyed dataset comparison on two sets of feature availability records (populated_features vs expected_features), returning two independent analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you deduplicate and compare these two feature availability datasets for me? The first set has rows like row-1 in group-a on 2026-10-01 with 10 populated features and 1 expected, and the second set has the same rows but with slightly different values — I need both a deduplication report and a keyed comparison report showing where they diverge.","exampleUseCases":[{"title":"ML pipeline feature completeness audit","prompt":"I have two snapshots of feature availability for my ML pipeline — the 'rows' dataset is what actually got populated, and the 'other' dataset is what was expected. Can you run exact row deduplication on both and give me a keyed comparison showing which dataset_group and date combinations have mismatches between populated_features and expected_features?"},{"title":"Detecting duplicate records in feature store","prompt":"My feature store export has 150 rows across groups A and B from 2026-09-01 through 2026-10-15. Can you deduplicate them by row_id and dataset_group and also compare them against my expected feature counts to see where things don't line up?"},{"title":"Dataset drift detection between two ETL runs","prompt":"I ran my ETL twice and got two slightly different feature availability outputs. Can you do an exact row dedup on both outputs and a keyed comparison using row_id, dataset_group, and date to flag rows where populated_features changed between the two runs?"}],"resultDescription":"Two independent analytical reports: (1) an exact row deduplication report identifying duplicate rows within each supplied dataset, and (2) a keyed dataset comparison report showing row-by-row differences between the 'rows' and 'other' input datasets based on populated_features and expected_features values. No external data sources or live lookups are used — all analysis is performed on the supplied data locally.","failureModes":["Input arrays exceed 200 rows — request rejected with validation error","Missing required fields (row_id, dataset_group, date, populated_features, expected_features) cause schema validation failure","Date field not matching YYYY-MM-DD pattern returns format error","row_id exceeding 80 characters triggers length validation error","Numeric values for populated_features or expected_features outside ±1,000,000,000,000 range rejected","Empty rows array (minItems:1 not met) returns validation error","Payment of 0.01 USDC not included or rejected causes 402 response"],"whenToPreferThis":"Choose this endpoint when you need both exact row deduplication and keyed dataset comparison on feature availability data in a single $0.01 call. It is ideal for ML/data engineering teams auditing feature store completeness, detecting ETL drift between two pipeline runs, or validating that populated feature counts match expected counts across dataset groups and dates — all without any external lookups or live data access. Prefer this over general-purpose data tools when your records conform to the row_id/dataset_group/date/populated_features/expected_features schema and you need two reports from one API call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T07:19:38.055Z","isFirstParty":false,"canonicalSlug":"feature-availability-exact-row-deduplication-keyed-dataset-comparison-fd0f3c05"}