{"uid":"cap_VgkyIK1uYr7ZXr2DHm7Bh","slug":"numeric-precision-comparisons-exact-row-deduplication-date-by-91c11bf7","name":"Numeric Precision Comparisons — Exact Row Deduplication + Date by Category Pivot","description":"Numeric precision comparisons — Exact row deduplication + Date by category pivot: Exact row deduplication + 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-20-052?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_CYEP4QVevfr61xZj2HN9k","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":"Performs exact row deduplication and date-by-category pivot analysis on up to 200 rows of numeric precision comparison records (source_value vs transformed_value), returning two independent analytical reports.","exampleAgentPrompt":"Can you deduplicate this set of numeric comparison records and also give me a date-by-category pivot? I have up to 50 rows with row_id, dataset_group, date, source_value, and transformed_value — I want both reports on the source_value field.","exampleUseCases":[{"title":"ETL pipeline validation deduplication","prompt":"I just ran an ETL job and got back 120 rows with original and transformed numeric values across two groups — can you deduplicate the exact rows and also pivot the source_value by date and group so I can see what changed?"},{"title":"Financial data transformation audit","prompt":"I have 80 records comparing raw financial figures against normalized values, each tagged with a date and a dataset_group. Run exact row deduplication and give me a date-by-category pivot on the transformed_value field."},{"title":"Data quality check before reporting","prompt":"Before I send this dataset to my manager, can you deduplicate it and pivot the source_value by date and category? It's got about 150 rows with source and transformed numeric columns plus group labels and dates."}],"resultDescription":"Two independent analytical reports: (1) an exact row deduplication report identifying and removing duplicate records from the supplied dataset, and (2) a date-by-category pivot report aggregating the selected numeric field (source_value or transformed_value) across dataset_group and date dimensions. Both are computed locally from the supplied rows with no external lookups.","failureModes":["More than 200 rows submitted — exceeds maxItems limit, request rejected","Missing required fields (row_id, dataset_group, date, source_value, transformed_value) on any row — validation error","Invalid date format not matching YYYY-MM-DD pattern — schema validation failure","Numeric values outside the range -1,000,000,000,000 to 1,000,000,000,000 — validation error","Invalid field enum value (not 'source_value' or 'transformed_value') — schema rejection","Empty rows array — minItems violation"],"whenToPreferThis":"Choose this endpoint when you need both exact row deduplication and a date-by-category pivot on numeric comparison data (source vs transformed values) in a single cheap call. It is ideal for data quality checks on ETL outputs, transformation audits, and pre-reporting cleanup where you have structured rows with a group label and date. It is not suitable for fuzzy deduplication, machine learning predictions, external data lookups, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:52.154Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-exact-row-deduplication-date-by-91c11bf7"}