{"uid":"cap_REHuVOBxhj571A1V24Clw","slug":"numeric-precision-comparisons-category-frequencies-trailing-mean-series-4666dbf6","name":"Numeric Precision Comparisons — Category Frequencies + Trailing Mean Series","description":"Numeric precision comparisons — Category frequencies + Trailing mean series: Category frequencies + Trailing mean series 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-20-103?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_YQ8MRJtfDdTE7WG635GMT","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 value pairs, producing two reports: category frequency counts by dataset group and a trailing mean time series over a configurable window.","exampleAgentPrompt":"Analyze my numeric precision comparison data — I have 150 rows with source_value and transformed_value fields across groups A and B — give me the category frequencies by dataset_group and a trailing mean series with a window of 5 for the transformed_value field.","exampleUseCases":[{"title":"ETL pipeline transformation audit","prompt":"I've got 120 rows from my ETL pipeline with original and transformed numeric values tagged by processing group — can you compute the category frequencies per group and a trailing mean series with window 10 on the source_value field so I can spot drift?"},{"title":"A/B test numeric output comparison","prompt":"I have two groups of numeric outputs from an A/B test, about 80 rows total with source_value as the control and transformed_value as the variant — run the category frequency report and a trailing mean with window size 3 on transformed_value."},{"title":"Data normalization quality check","prompt":"After running our normalization step I have 200 rows of before/after values grouped by data_type — generate the group frequency breakdown and a rolling mean series with window 7 on source_value so I can verify the normalization is behaving consistently."}],"resultDescription":"Returns two independent analytical reports: (1) category frequency counts showing how many rows belong to each dataset_group, and (2) a trailing mean time series computed over the specified rolling window for the selected field (source_value or transformed_value), all derived from the supplied rows without any external lookups.","failureModes":["Fewer than 1 row supplied — validation error","More than 200 rows submitted — input rejected at maxItems limit","Window size exceeds number of rows — trailing mean may produce partial or no results","Invalid date format (not YYYY-MM-DD) — schema validation failure","source_value or transformed_value outside ±1,000,000,000,000 range — validation error","Invalid field enum value — request rejected","Payment not included or insufficient — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need both a group-level frequency distribution and a rolling mean time series computed together on the same dataset of numeric source/transformed value pairs, without requiring any external data sources or live lookups. Ideal for data quality checks, ETL audits, and transformation validation workflows where you want two complementary statistical views in a single low-cost call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:39:55.474Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-category-frequencies-trailing-mean-series-4666dbf6"}