{"uid":"cap_lMKZv8iJ2_fJFLOlcR2pQ","slug":"feature-availability-analytics-exact-row-deduplication-base-100-series-ad446a26","name":"Feature Availability Analytics — Exact Row Deduplication + Base-100 Series","description":"Feature availability — Exact row deduplication + Base-100 series: Exact row deduplication + Base-100 series 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-10-047?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":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_WrBSM-j_FXiSoskyeo_se","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":"Runs exact row deduplication and a base-100 indexed series report on up to 200 feature availability records (populated_features vs expected_features) using local analytical engines.","exampleAgentPrompt":"Can you deduplicate these feature availability records and produce a base-100 index series on populated_features, starting the index at row 0? I have about 50 rows across two dataset groups covering October 2026.","exampleUseCases":[{"title":"Deduplicating ML pipeline feature logs","prompt":"I have 120 rows of daily feature availability logs from our ML pipeline with populated_features and expected_features columns — can you remove exact duplicate rows and give me a base-100 series on populated_features, anchoring the index at row 0?"},{"title":"Monitoring feature completeness over time","prompt":"Run an indexed series report on expected_features for my 80-row dataset, using base index position 0, so I can see how feature expectations have trended relative to that starting point across my two dataset groups."},{"title":"Auditing dataset group feature fill rates","prompt":"I need to audit feature fill rates across group-a and group-b for Q4 2026 — can you deduplicate my 200 feature availability records and generate a base-100 series on populated_features anchored at index 0?"}],"resultDescription":"Returns two analytical reports for the supplied rows: (1) an exact row deduplication result identifying and removing duplicate records, and (2) a base-100 indexed series for the selected field (populated_features or expected_features), anchored at the specified base_index row. Both reports are computed locally without external lookups.","failureModes":["Input exceeds 200 rows — request rejected","Missing required fields (row_id, date, populated_features, expected_features) — validation error","Invalid date format (not YYYY-MM-DD) — schema rejection","base_index out of range (0–199) — parameter error","All rows are duplicates leaving empty result set","null values in numeric fields may affect series computation"],"whenToPreferThis":"Choose this endpoint when you need both exact duplicate row removal and a base-100 normalized index series on feature availability data in a single low-cost call. Ideal for data quality audits on small-to-medium datasets (≤200 rows) where no live lookup or prediction is needed — purely supply-your-own-data analytical computation at $0.01 USDC per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T01:00:13.388Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-exact-row-deduplication-base-100-series-ad446a26"}