{"uid":"cap_Yg4ZGkmG28NLS_GjkEpQ3","slug":"numeric-precision-comparisons-daily-sum-series-date-by-category-pivot-01465fc8","name":"Numeric Precision Comparisons — Daily Sum Series + Date by Category Pivot","description":"Numeric precision comparisons — Daily sum series + Date by category pivot: Daily sum series + 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-20-143?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_WO7X7bc5cSH5dbRVqlxPX","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":"Generates two analytical reports (daily sum time series and date-by-category pivot table) from user-supplied numeric precision comparison data (source_value vs transformed_value) for up to 200 rows.","exampleAgentPrompt":"Can you run two analytics reports on my numeric comparison data — a daily sum time series and a date-by-category pivot — using source_value as the field? I have 4 rows: row-1 on 2026-10-01 with source 10 and transformed 1 in group-a, row-2 on 2026-10-02 with source 20 and transformed 2 in group-b, row-3 on 2026-10-03 with source 15 and transformed 3 in group-a, and row-4 on 2026-10-04 with source 30 and transformed 4 in group-b.","exampleUseCases":[{"title":"ETL pipeline accuracy audit","prompt":"I ran an ETL job on our sales figures and I need to compare source_value versus transformed_value across 150 records by date and business unit — can you give me a daily sum series and a category pivot to see where the numbers diverge?"},{"title":"Daily revenue transformation check","prompt":"Here are 80 rows of revenue data with dates, group names, and both raw and transformed amounts — can you generate a daily sum time series and a date-by-category pivot table on the source_value field so I can spot any anomalies?"},{"title":"Data quality report for model inputs","prompt":"I have 200 rows of model input records spanning October, each with a source value and a transformed value labeled by dataset group — can you produce a daily aggregate series and a pivot by category and date on the transformed_value field?"}],"resultDescription":"Returns two independent analytical reports computed from the supplied rows: (1) a daily sum series showing totals of the selected field (source_value or transformed_value) aggregated by date, and (2) a date-by-category pivot table cross-tabulating the selected field by date and dataset_group. No external data is fetched; all computation is done on the provided rows (up to 200).","failureModes":["Fewer than 1 row or more than 200 rows causes a validation error","Malformed date strings (not YYYY-MM-DD) are rejected","source_value or transformed_value outside ±1,000,000,000,000 are rejected","Missing required fields (row_id, dataset_group, date) cause schema validation failure","Invalid field enum value (anything other than 'source_value' or 'transformed_value') is rejected"],"whenToPreferThis":"Choose this endpoint when you have a batch of numeric records with source and transformed values organized by date and category, and you need both a time-series daily aggregate and a cross-tabulated pivot in a single call. Ideal for ETL auditing, data transformation QA, and precision drift analysis where you want two complementary views without setting up a local analytics environment. Best suited for datasets up to 200 rows where a quick, low-cost ($0.01 USDC) dual-report is sufficient.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:47.119Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-daily-sum-series-date-by-category-pivot-01465fc8"}