{"uid":"cap_lK4Z82cekUdxyU3P7ck3P","slug":"dataset-storage-numeric-interval-filter-and-iqr-outlier-flags-46daf891","name":"Dataset Storage Numeric Interval Filter and IQR Outlier Flags","description":"Dataset storage — Numeric interval filter + IQR outlier flags: Numeric interval filter + 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-18-130?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"},"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_AcvH2F85M2eRoPhJDR-PJ","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":"Filters dataset storage records by a numeric interval and flags IQR-based outliers for used_mb or row_count fields across up to 200 rows.","exampleAgentPrompt":"Can you filter my dataset storage records to only show rows where used_mb is between 0 and 500, and also flag any IQR outliers in the used_mb field? Here are my rows: row-1 group-a 2026-10-01 used_mb=10 row_count=100, row-2 group-b 2026-10-02 used_mb=950 row_count=200, row-3 group-a 2026-10-03 used_mb=20 row_count=150.","exampleUseCases":[{"title":"Storage anomaly detection for data pipeline","prompt":"I have 50 daily storage snapshots from my data pipeline — can you flag any rows where used_mb looks like an outlier using IQR, and also filter to only show records where used_mb is between 10 and 800? The field I care about is used_mb."},{"title":"Row count audit across dataset groups","prompt":"Run an interval filter and IQR outlier check on these dataset records using the row_count field — keep only rows where row_count is between 100 and 50000 and flag anything that's an outlier. I've got about 120 rows across three dataset groups."},{"title":"Identifying unusual storage growth","prompt":"Here are my monthly dataset storage records going back 6 months — can you filter used_mb between 0 and 200 and tell me which rows are IQR outliers in used_mb so I can investigate unexpected storage spikes?"}],"resultDescription":"Returns two reports for the supplied dataset rows: (1) a numeric interval filter report showing which rows fall within the specified minimum/maximum range for the chosen field, and (2) an IQR outlier flags report identifying rows whose values fall outside the interquartile range for that field. Both reports are computed locally on the supplied data with no external lookups.","failureModes":["Fewer than 1 row or more than 200 rows supplied — request rejected","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Null values in used_mb or row_count may affect IQR computation or be excluded","Minimum greater than maximum results in empty interval filter output","Missing required fields (row_id, dataset_group, date) cause validation errors","Field enum value not one of used_mb or row_count causes rejection"],"whenToPreferThis":"Choose this endpoint when you need to simultaneously filter dataset storage records by a numeric range AND detect IQR-based statistical outliers on the same dataset, with up to 200 rows, at very low cost ($0.01 USDC for both reports). It is best suited for offline/batch analytical tasks on pre-collected storage metrics (used_mb, row_count) where no live data fetching, prediction, or external enrichment is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:54.816Z","isFirstParty":false,"canonicalSlug":"dataset-storage-numeric-interval-filter-and-iqr-outlier-flags-46daf891"}