{"uid":"cap_TZuhkYdZ_R3ILHtXSCr3V","slug":"dataset-storage-analytics-adjacent-row-changes-iqr-outlier-flags-2f841f0a","name":"Dataset Storage Analytics: Adjacent Row Changes + IQR Outlier Flags","description":"Dataset storage — Adjacent row changes + IQR outlier flags: Adjacent row changes + 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-18-157?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_jlFejGLvy12lHffqU1gfL","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":"Analyzes up to 200 dataset storage records to produce two reports: adjacent row-to-row changes and IQR-based outlier flags for used_mb or row_count fields.","exampleAgentPrompt":"Analyze these storage records for adjacent row changes and IQR outlier flags on the used_mb field — I have rows with dates from 2026-10-01 to 2026-10-04, groups group-a and group-b, with usage values like 10, 20, 15, 30 MB and row counts 1 through 4.","exampleUseCases":[{"title":"Storage spike detection in daily snapshots","prompt":"I have daily storage snapshots for my datasets from the past month — can you check the used_mb field for IQR outliers and flag any days where storage jumped dramatically compared to the previous row?"},{"title":"Row count anomaly audit across dataset groups","prompt":"Run an adjacent row change analysis and IQR outlier check on the row_count field for these 150 records across my dataset groups — I want to know which rows look statistically abnormal."},{"title":"Pre-migration data quality check","prompt":"Before I migrate these dataset records, can you flag any outliers and unusual jumps in used_mb using IQR analysis and adjacent row comparisons? I have about 80 records with dates and group labels."}],"resultDescription":"Returns two analytical reports for the supplied dataset storage rows: (1) an adjacent row change report showing delta values between consecutive rows for the selected field, and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range. No external data is fetched; all analysis is performed locally on the supplied records.","failureModes":["Exceeds 200 row limit — request rejected","Missing required fields (row_id, date, used_mb, row_count, dataset_group) — validation error","Invalid date format (must be YYYY-MM-DD) — schema rejection","Invalid field enum value (must be 'used_mb' or 'row_count') — error","Numeric values out of allowed range — validation failure","Empty rows array — schema rejection"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local statistical analysis of dataset storage metrics (used_mb or row_count) without any external lookups or predictions. It is ideal for data quality checks, anomaly pre-screening, and storage trend monitoring on batches of up to 200 rows. Prefer it over general-purpose analytics platforms when you want a fast, low-cost ($0.01 USDC for both reports) offline computation against your own supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:40.267Z","isFirstParty":false,"canonicalSlug":"dataset-storage-analytics-adjacent-row-changes-iqr-outlier-flags-2f841f0a"}