{"uid":"cap_DNQPUIyDntKdCOD_BT4yE","slug":"dataset-storage-numeric-row-ordering-iqr-outlier-flags-37bced0f","name":"Dataset Storage — Numeric Row Ordering + IQR Outlier Flags","description":"Dataset storage — Numeric row ordering + IQR outlier flags: Numeric row ordering + IQR outlier flags for supplied dataset storage records (used_mb, row_count). 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-18-119?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","used_mb","row_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"used_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","used_mb":10,"row_count":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","used_mb":20,"row_count":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","used_mb":15,"row_count":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","used_mb":30,"row_count":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["used_mb","row_count"],"type":"string","default":"used_mb"}}},"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_sXBVyySWAcvu92Rmt8L9i","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":"Sorts dataset storage records by a numeric field (used_mb or row_count) and flags outliers using the interquartile range (IQR) method, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you rank these storage records by used_mb and flag any IQR outliers? I have up to 50 rows with fields row_id, dataset_group, date, used_mb, and row_count — here's the data.","exampleUseCases":[{"title":"Storage audit for data platform team","prompt":"I've got 120 dataset storage snapshots with used_mb and row_count per group — can you sort them by used_mb and flag anything that looks like an outlier using IQR? I want to know which partitions are abnormally large."},{"title":"Row count anomaly detection across pipeline stages","prompt":"Here are 80 pipeline stage records with row counts by date and group. Sort them by row_count and use IQR to flag any stages that produced suspiciously high or low row counts."},{"title":"Monthly storage usage review","prompt":"I have this month's dataset storage records — 60 rows with used_mb per dataset group. Can you order them by used_mb and generate an IQR outlier report so I can spot which groups are consuming unexpectedly large amounts of storage?"}],"resultDescription":"Returns two analytical reports: (1) the input rows sorted in numeric order by the selected field (used_mb or row_count), and (2) IQR-based outlier flags identifying which rows fall below Q1−1.5×IQR or above Q3+1.5×IQR. No external lookups or predictions are made — all analysis is performed locally on the supplied data.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds limit","Missing required fields (row_id, dataset_group, date, used_mb, row_count) — validation error","Invalid date format (must match YYYY-MM-DD) — schema rejection","All values null for selected field — IQR computation not possible","Field selector not one of 'used_mb' or 'row_count' — enum validation failure"],"whenToPreferThis":"Choose this endpoint when you have up to 200 dataset storage records with numeric used_mb or row_count fields and need both a sorted ranking and IQR-based outlier detection in a single low-cost call ($0.01 USDC). It is ideal for data quality checks, storage audits, and anomaly flagging on already-collected data — not for live monitoring, predictions, or external data lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:28.742Z","isFirstParty":false,"canonicalSlug":"dataset-storage-numeric-row-ordering-iqr-outlier-flags-37bced0f"}