{"uid":"cap_717iYNoqVzd3uBF7-gRuM","slug":"numeric-precision-comparisons-adjacent-row-changes-two-measure-5366ef7c","name":"Numeric Precision Comparisons — Adjacent Row Changes + Two-Measure Correlation","description":"Numeric precision comparisons — Adjacent row changes + Two-measure correlation: Adjacent row changes + Two-measure correlation 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-20-158?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_mSIeBvVSrnrPtI1SlBXgy","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, producing two local reports: adjacent row change deltas and two-measure correlation between source_value and transformed_value.","exampleAgentPrompt":"Can you run adjacent row change analysis and correlation between source_value and transformed_value on my dataset — I have 4 rows: row-1 on 2026-10-01 (source 10, transformed 1), row-2 on 2026-10-02 (source 20, transformed 2), row-3 on 2026-10-03 (source 15, transformed 3), row-4 on 2026-10-04 (source 30, transformed 4), all in group-a — and use source_value as the primary field?","exampleUseCases":[{"title":"ETL pipeline numeric audit","prompt":"I ran a data transformation on my sales figures and want to check how much each row changed versus the previous one, and whether the source and output values are correlated — here are 50 rows with dates, row IDs, source values, and transformed values, all tagged group-sales. Use source_value as the field."},{"title":"Financial model output validation","prompt":"Can you analyze these 120 rows from my financial model — each has a date, a source_value from the raw feed, and a transformed_value after our normalization step — and give me both the adjacent row deltas and the correlation between the two measures? Dataset group is 'finance-q3'."},{"title":"Sensor data transformation check","prompt":"I have sensor readings before and after calibration, 80 rows grouped under 'sensor-lab', each with a date, row ID, source_value (raw), and transformed_value (calibrated). Can you compute the row-to-row changes and tell me how correlated the raw and calibrated values are?"}],"resultDescription":"Returns two independent analytical reports computed locally from the supplied rows: (1) adjacent row changes showing the delta between consecutive rows for the selected field, and (2) two-measure correlation between source_value and transformed_value across all supplied rows. No external lookups or predictions are made.","failureModes":["More than 200 rows submitted — request exceeds maxItems limit","Missing required fields (row_id, date, source_value, transformed_value, dataset_group) cause validation errors","Date strings not matching YYYY-MM-DD pattern are rejected","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array (minItems:1 not met) causes failure","Invalid field enum value (not 'source_value' or 'transformed_value') causes error"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, local statistical analysis of paired numeric columns (source vs transformed) without sending data to an external prediction or ML service. Ideal for auditing ETL pipelines, data quality checks, or transformation validation where you want both row-to-row delta inspection and a correlation report in a single $0.01 call for up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:57.595Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-adjacent-row-changes-two-measure-5366ef7c"}