{"uid":"cap_Gao9kxMeNf_eTtXOQvqAs","slug":"feature-availability-analytics-exact-row-deduplication-date-by-c89ee1ef","name":"Feature Availability Analytics — Exact Row Deduplication + Date by Category Pivot","description":"Feature availability — Exact row deduplication + Date by category pivot: Exact row deduplication + Date by category pivot 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-10-052?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},"field":{"enum":["populated_features","expected_features"],"type":"string","default":"populated_features"}}},"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_k5amvxA6TTw1DfswqM3hF","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 date-by-category pivot analysis on supplied feature availability records (populated_features, expected_features) for up to 200 rows.","exampleAgentPrompt":"I have feature availability records for two dataset groups — group-a and group-b — with dates, populated_features, and expected_features columns. Can you run exact row deduplication and a date-by-category pivot on those rows so I can see clean counts and a crosstab summary? Use populated_features as the pivot field.","exampleUseCases":[{"title":"Feature coverage audit by dataset group","prompt":"I have up to 150 rows of feature availability data with dataset_group, date, populated_features, and expected_features. Can you deduplicate any exact duplicate rows and then give me a pivot table showing populated_features by date and group so I can see where coverage is missing?"},{"title":"Data pipeline deduplication before model training","prompt":"Before I feed this feature store data into my training pipeline, I need to strip out any exact duplicate records and get a date-by-category breakdown of expected_features. Here are my rows with row_id, dataset_group, date, and feature counts — please run both reports."},{"title":"Weekly feature availability QA report","prompt":"Can you take these weekly feature availability records across group-a and group-b and produce both an exact duplicate check and a pivot of expected_features by date and dataset_group? I want to catch any duplicate logging and see the weekly rollup in one shot."}],"resultDescription":"Returns two analytical reports: (1) a deduplicated version of the supplied rows with exact duplicates removed, and (2) a date-by-category pivot table showing the selected field (populated_features or expected_features) broken down by date and dataset_group. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Exceeds 200 row limit — request rejected","Missing required fields (row_id, date, dataset_group, populated_features, expected_features) — validation error","Invalid date format (must match YYYY-MM-DD) — pattern validation failure","Field value out of numeric range (±1,000,000,000,000) — schema rejection","Empty rows array — minItems violation","Payment not completed or insufficient USDC — 402 response"],"whenToPreferThis":"Choose this endpoint when you need fast, offline analytical processing of feature availability records — specifically exact row deduplication combined with a date-by-category pivot — on a small-to-medium dataset (up to 200 rows) without requiring any live data lookups, predictions, or external integrations. It is ideal for data quality checks in ML pipelines, feature store audits, or ETL validation steps where two bundled reports are needed cost-effectively at $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:36.103Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-exact-row-deduplication-date-by-c89ee1ef"}