{"uid":"cap_2zf5I7NlGIuQc5HM43EH2","slug":"numeric-precision-comparisons-adjacent-row-changes-iqr-outlier-flags-3ffd574d","name":"Numeric Precision Comparisons — Adjacent Row Changes + IQR Outlier Flags","description":"Numeric precision comparisons — Adjacent row changes + IQR outlier flags: Adjacent row changes + IQR outlier flags for supplied numeric precision comparisons records (source_value, transformed_value). 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-20-157?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","source_value","transformed_value"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"transformed_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_value":10,"dataset_group":"group-a","transformed_value":1},{"date":"2026-10-02","row_id":"row-2","source_value":20,"dataset_group":"group-b","transformed_value":2},{"date":"2026-10-03","row_id":"row-3","source_value":15,"dataset_group":"group-a","transformed_value":3},{"date":"2026-10-04","row_id":"row-4","source_value":30,"dataset_group":"group-b","transformed_value":4}],"maxItems":200,"minItems":1},"field":{"enum":["source_value","transformed_value"],"type":"string","default":"source_value"}}},"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_9cMx-u3mH6y3r5-mWRMQZ","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 rows of source/transformed numeric pairs to detect adjacent-row changes and flag IQR-based outliers, producing two independent analytical reports per call.","exampleAgentPrompt":"Analyze these 50 rows of source and transformed sales figures — field is source_value — and give me both the adjacent row change report and the IQR outlier flags so I can see which rows have unusual jumps or are statistical outliers.","exampleUseCases":[{"title":"ETL pipeline data quality check","prompt":"I have 120 rows of ETL output with source_value and transformed_value fields — run adjacent row change detection and IQR outlier flagging on the source_value column so I can spot any transformation errors before we push to production."},{"title":"Financial time series anomaly detection","prompt":"Here are 80 daily revenue records from 2024-01-01 to 2024-03-21 — check the transformed_value field for IQR outliers and adjacent row changes so I know which days had abnormal revenue swings."},{"title":"Sensor reading validation","prompt":"I've got 150 sensor readings across two groups — can you run the adjacent row changes and IQR outlier reports on source_value to flag any readings that look like sensor errors or sudden spikes?"}],"resultDescription":"Two independent analytical reports: (1) an adjacent row change report showing delta values between consecutive rows, and (2) an IQR outlier flags report identifying which rows fall outside the interquartile range boundary — all computed locally without external lookups, covering up to 200 input rows.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, source_value, transformed_value) — validation error","date field does not match YYYY-MM-DD pattern — schema validation failure","source_value or transformed_value out of allowed range (±1 trillion) — rejected","Payment of 0.01 USDC not received — 402 Payment Required","Empty rows array — schema minItems violation"],"whenToPreferThis":"Choose this endpoint when you need fast, local (no external data fetched) statistical analysis of numeric paired records — specifically adjacent row change detection AND IQR outlier flagging delivered together in one call for up to 200 rows at very low cost. Ideal for data quality pipelines, ETL validation, and time-series anomaly screening where you control the input data and need two complementary views on numeric variation.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:39:41.244Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-adjacent-row-changes-iqr-outlier-flags-3ffd574d"}