{"uid":"cap_MAUTiLsagWuu7g8OWpDFo","slug":"feature-availability-analytics-category-frequencies-numeric-interval-8f469159","name":"Feature Availability Analytics — Category Frequencies & Numeric Interval Filter","description":"Feature availability — Category frequencies + Numeric interval filter: Category frequencies + Numeric interval filter 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-10-101?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_0ZPHIK-d71B4-kZ7UibVm","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":"Computes category frequencies and applies a numeric interval filter on supplied feature availability records (populated_features / expected_features) for up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Analyze my feature availability dataset — I have up to 50 rows with populated_features and expected_features per dataset_group and date — give me the category frequencies by group and also filter rows where populated_features falls between 5 and 100.","exampleUseCases":[{"title":"Feature completeness audit by group","prompt":"I have feature availability records for two groups, 'train' and 'test', across 30 dates. Can you show me the category frequency breakdown by dataset_group and filter the populated_features field to only show rows between 10 and 500?"},{"title":"Detecting under-populated feature rows","prompt":"I want to find which rows in my feature availability dataset have populated_features between 0 and 20 — I have 80 rows across groups 'prod' and 'staging'. Also give me the frequency of each group in the data."},{"title":"Expected features range analysis","prompt":"Run a numeric interval filter on the expected_features field for my 120-row dataset, keeping only rows between 50 and 200, and give me category frequencies by dataset_group at the same time."}],"resultDescription":"Returns two independent analytical reports: (1) category frequency counts broken down by dataset_group across the supplied rows, and (2) a filtered subset of rows where the selected numeric field (populated_features or expected_features) falls within the specified minimum–maximum interval. Both reports are computed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — exceeds maxItems limit, request rejected","Missing required fields (row_id, date, populated_features, expected_features) — validation error","Date field does not match YYYY-MM-DD pattern — schema validation failure","Minimum or maximum values outside allowed numeric range — validation error","Empty rows array — minItems constraint violated","Payment not included or insufficient — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need two simultaneous lightweight analytical reports — category frequency counts and a numeric range filter — on feature availability data (populated_features / expected_features) without requiring any external data sources, predictions, or live lookups. It is ideal for data quality workflows where you want to audit feature completeness across dataset groups and quickly identify rows within a specific numeric band, all within a single low-cost ($0.01 USDC) call covering up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:46.082Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-category-frequencies-numeric-interval-8f469159"}