{"uid":"cap_9jD7GcRT1X2YocFCYrgOh","slug":"data-ingestion-batches-numeric-distribution-trailing-mean-series-93579192","name":"Data Ingestion Batches — Numeric Distribution + Trailing Mean Series","description":"Data ingestion batches — Numeric distribution + Trailing mean series: Numeric distribution + Trailing mean series for supplied data ingestion batches records (received_rows, accepted_rows). 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-01-076?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","received_rows","accepted_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"accepted_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"received_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","accepted_rows":1,"dataset_group":"group-a","received_rows":10},{"date":"2026-10-02","row_id":"row-2","accepted_rows":2,"dataset_group":"group-b","received_rows":20},{"date":"2026-10-03","row_id":"row-3","accepted_rows":3,"dataset_group":"group-a","received_rows":15},{"date":"2026-10-04","row_id":"row-4","accepted_rows":4,"dataset_group":"group-b","received_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["received_rows","accepted_rows"],"type":"string","default":"received_rows"},"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_2C2Thw8CEkguNDUWLwtE5","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":"Computes a numeric distribution report and a trailing mean time series for received_rows or accepted_rows across up to 200 data ingestion batch records.","exampleAgentPrompt":"Analyze these 50 ingestion batch records and give me both a numeric distribution and a trailing mean series for the received_rows field using a window of 7 — here's the data: [{\"row_id\":\"r1\",\"dataset_group\":\"group-a\",\"date\":\"2026-01-01\",\"received_rows\":100,\"accepted_rows\":95}, ...]","exampleUseCases":[{"title":"ETL pipeline acceptance rate analysis","prompt":"I have 120 daily ingestion batch records from our ETL pipeline — can you compute the numeric distribution and trailing mean series for accepted_rows with a window of 14? I want to spot patterns in how many rows we're accepting each day."},{"title":"Data quality monitoring over batches","prompt":"Here are 80 ingestion batch records split across two dataset groups. Run both a numeric distribution and a trailing mean series on received_rows with a window of 5 so I can see if our ingestion volumes have been stable."},{"title":"Ingestion volume trend reporting","prompt":"I need a report on our ingestion batch volumes from the last quarter — can you take these 200 batch records and compute the numeric distribution plus a 10-day trailing mean for received_rows so I can see the trend?"}],"resultDescription":"Returns two analytical reports: (1) a numeric distribution summarizing the statistical spread (e.g. min, max, mean, percentiles, histogram) of the selected field (received_rows or accepted_rows), and (2) a trailing mean time series showing the rolling average over the specified window size, both computed locally against the supplied batch records.","failureModes":["Fewer than 1 row supplied — minimum 1 row required","More than 200 rows supplied — maxItems limit exceeded","Invalid date format in any row — must match YYYY-MM-DD","Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) in any row","Window size outside range 2–200 — validation error","Field value not one of 'received_rows' or 'accepted_rows' — enum validation failure","Payment not provided or insufficient — x402 payment required before processing"],"whenToPreferThis":"Choose this endpoint when you have up to 200 data ingestion batch records and need both a numeric distribution summary and a trailing mean time series in a single low-cost call ($0.01 USDC). Ideal for data engineers and pipeline operators who want quick local statistical analysis of received_rows or accepted_rows without connecting to an external database or analytics platform. Prefer this over building custom analytics when you want two complementary views (distribution shape + rolling trend) bundled together efficiently.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:38.688Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-numeric-distribution-trailing-mean-series-93579192"}