{"uid":"cap_cPe7htCBFFUpCwzXa7jhE","slug":"numeric-precision-comparisons-iqr-outlier-flags-secondary-measure-5c8ff3cd","name":"Numeric Precision Comparisons — IQR Outlier Flags + Secondary-Measure Weighted Mean","description":"Numeric precision comparisons — IQR outlier flags + Secondary-measure weighted mean: IQR outlier flags + Secondary-measure weighted mean 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-20-177?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_h10K6zwOJ5OOQyA8ZyFiY","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 value pairs, flagging IQR-based outliers and computing a secondary-measure weighted mean in two independent local analytical reports.","exampleAgentPrompt":"Can you run IQR outlier detection and a weighted mean calculation on these 50 rows of source and transformed values — the dataset group is 'sales-q3', dates range from 2025-01-01 to 2025-03-31, and I want the analysis run on source_value?","exampleUseCases":[{"title":"ETL pipeline data quality check","prompt":"I just ran an ETL job transforming 120 revenue records — can you flag any IQR outliers and compute the weighted mean across the source_value column so I can spot which rows got mangled during transformation?"},{"title":"Financial data anomaly review","prompt":"Here are 80 rows of financial measurements with their original and adjusted values, grouped by region and dated from 2024-07-01 to 2024-09-30 — please flag any IQR-based outliers and give me the weighted mean for the transformed_value field."},{"title":"Sensor reading precision audit","prompt":"I have 150 sensor readings where source_value is the raw reading and transformed_value is the calibrated output — run IQR outlier flags and a secondary weighted mean on the source_value field so I can see which sensors are behaving erratically."}],"resultDescription":"Returns two independent analytical reports for the submitted rows: (1) IQR outlier flags identifying which rows fall outside the interquartile range for the selected field, and (2) a secondary-measure weighted mean computed across the dataset. All analysis is performed locally with no external lookups or predictions.","failureModes":["More than 200 rows submitted — request rejected with validation error","Missing required fields (row_id, dataset_group, date, source_value, transformed_value) — schema validation failure","Invalid date format (not YYYY-MM-DD) — pattern validation error","Numeric values outside allowed range (±1,000,000,000,000) — validation rejection","Empty rows array — minItems constraint violation","All values null for selected field — statistical computation may return undefined results"],"whenToPreferThis":"Choose this endpoint when you need fast, local statistical analysis on a batch of up to 200 numeric source/transformed value pairs — specifically IQR-based outlier detection plus weighted mean — without any external data lookups, ML predictions, or professional assessment. Ideal for data quality audits on ETL pipelines, sensor calibration checks, or financial data reconciliation where you need two standard statistical reports in a single low-cost call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:55.431Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-iqr-outlier-flags-secondary-measure-5c8ff3cd"}