{"uid":"cap_xgsvb5aRpWw3zVYAcye1v","slug":"numeric-precision-comparisons-analytics-record-quality-audit-string-54ed09b4","name":"Numeric Precision Comparisons Analytics — Record Quality Audit + String Normalisation + Trailing Mean Series","description":"Numeric precision comparisons — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series for supplied numeric precision comparisons records (source_value, transformed_value). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-199?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_UGQacsf6-NMPl6ZVlDGrC","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":"Runs three local analytical reports (record quality audit, string normalisation, and trailing mean series) on up to 200 rows of numeric source/transformed value pairs.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and trailing mean series (window size 3) on my numeric data rows — I have source_value and transformed_value pairs for groups A and B across dates in October 2026, up to 50 rows total, analysing the source_value field?","exampleUseCases":[{"title":"ETL pipeline transformation audit","prompt":"I just ran an ETL job and I need to check the quality of the transformation — can you run a record quality audit and trailing mean series with a window of 5 on my 80 rows of source_value and transformed_value pairs from the 'sales' dataset group, analysing the transformed_value field?"},{"title":"Rolling average on sensor readings","prompt":"I have 120 rows of sensor readings with source_value and transformed_value columns across three device groups from November 2025. Can you compute a trailing mean series with window size 10 on the source_value field and also give me the quality audit and string normalisation reports?"},{"title":"Data normalisation check before reporting","prompt":"Before I publish my monthly report, I want to verify numeric precision — can you run all three analytics reports (quality audit, string normalisation, trailing mean window 4) on my 35 rows of finance data comparing raw source_value figures to transformed_value outputs across the 'revenue' and 'cost' dataset groups?"}],"resultDescription":"Returns three independent reports: (1) a record quality audit flagging data issues in the supplied rows, (2) a string normalisation report on the row/group fields, and (3) a trailing mean time series computed over the selected numeric field (source_value or transformed_value) with the specified window size. All analysis is performed locally with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — validation error","Missing required row fields (row_id, dataset_group, date, source_value, transformed_value) — schema rejection","Invalid date format (not YYYY-MM-DD) — pattern validation error","Window size outside 2–200 range — validation error","Numeric values outside ±1,000,000,000,000 — schema rejection","Payment not included or insufficient — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need three simultaneous analytical reports on a small-to-medium dataset (up to 200 rows) of numeric source/transformed value pairs without requiring any external data lookups, live predictions, or professional assessments. It is ideal for ETL validation, data quality checks, and rolling average computation in a single low-cost call ($0.01 USDC for all three reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:07.173Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-analytics-record-quality-audit-string-54ed09b4"}