{"uid":"cap_oVb5VzX-v1rhCSOMUFEDq","slug":"numeric-precision-comparisons-adjacent-row-changes-date-by-category-2f7b23bd","name":"Numeric Precision Comparisons — Adjacent Row Changes + Date by Category Pivot","description":"Numeric precision comparisons — Adjacent row changes + Date by category pivot: Adjacent row changes + Date by category pivot 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-20-160?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__3VxOhKTAJPAjHLloSXoV","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 two local analytical reports on up to 200 rows of numeric precision comparison data: adjacent row-to-row change analysis and a date-by-category pivot table, covering source_value and transformed_value fields.","exampleAgentPrompt":"I have a table of up to 200 rows with source_value and transformed_value measurements across different dataset groups and dates — can you run adjacent row change analysis and a date-by-category pivot on the source_value field for me?","exampleUseCases":[{"title":"ETL pipeline validation review","prompt":"I've got 150 rows from my ETL pipeline with original and transformed numeric values tagged by group and date. Can you show me the row-over-row changes and a pivot of source_value by date and dataset group so I can spot where the transformation went wrong?"},{"title":"Financial data precision audit","prompt":"Here are 200 rows of financial figures with source and transformed amounts across several reporting groups from October 2026. Run adjacent row change analysis and a date-by-category pivot on the transformed_value field so I can audit the precision differences."},{"title":"Sensor reading delta tracking","prompt":"I have sensor readings for two device groups across 80 daily timestamps, each with a raw source_value and a calibrated transformed_value. Can you compute the adjacent row changes and pivot the source_value by date and group so I can see how readings shift over time?"}],"resultDescription":"Two independent analytical reports: (1) adjacent row changes showing sequential numeric deltas between consecutive rows for the selected field, and (2) a date-by-category pivot table grouping the selected field's values by date and dataset_group. Results are computed locally from the supplied data with no external lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, dataset_group, date, source_value, transformed_value) on any row — validation error","Date fields not matching YYYY-MM-DD pattern — schema validation failure","Numeric values outside ±1,000,000,000,000 range — schema rejection","Empty rows array — minimum item count not met","Invalid field enum value (must be source_value or transformed_value) — schema error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of paired numeric data (source and transformed values) tagged with dates and group labels, and you need both sequential delta analysis and a date-by-category pivot in a single low-cost call. It is ideal for ETL validation, data transformation audits, or any scenario where you want two complementary analytical views on the same numeric precision dataset without external dependencies or live data lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:37.983Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-adjacent-row-changes-date-by-category-2f7b23bd"}