{"uid":"cap_d7DMRDH8PVd_WKyIqWo0d","slug":"null-coverage-analytics-trailing-mean-series-adjacent-row-changes-3b758dfb","name":"Null Coverage Analytics — Trailing Mean Series + Adjacent Row Changes","description":"Null coverage — Trailing mean series + Adjacent row changes: Trailing mean series + Adjacent row changes for supplied null coverage records (missing_values, total_values). 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-03-146?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","missing_values","total_values"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"missing_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_values":1,"dataset_group":"group-a","missing_values":10},{"date":"2026-10-02","row_id":"row-2","total_values":2,"dataset_group":"group-b","missing_values":20},{"date":"2026-10-03","row_id":"row-3","total_values":3,"dataset_group":"group-a","missing_values":15},{"date":"2026-10-04","row_id":"row-4","total_values":4,"dataset_group":"group-b","missing_values":30}],"maxItems":200,"minItems":1},"field":{"enum":["missing_values","total_values"],"type":"string","default":"missing_values"},"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_HMzS7guI0s9e1AcXc1mcV","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 trailing mean time series and adjacent row-to-row changes for null coverage data (missing_values, total_values) over up to 200 supplied rows.","exampleAgentPrompt":"I have 50 rows of null coverage records with dates, dataset groups, missing_values and total_values — can you run a trailing mean series and adjacent row changes report on the missing_values field using a window size of 5?","exampleUseCases":[{"title":"Data quality trend monitoring","prompt":"I've got daily null coverage records for our ETL pipeline across 120 rows — can you compute the trailing mean series and adjacent changes for the missing_values field using a window of 7 so I can spot where data quality is degrading?"},{"title":"Dataset group comparison over time","prompt":"Here are 80 rows of null coverage data split across two dataset groups. Run a trailing mean and row-to-row change report on total_values with a window of 3 so I can compare completeness trends between groups."},{"title":"Sudden spike detection in missing data","prompt":"I have 40 rows of null coverage records from last month. Can you produce the adjacent row changes and trailing mean series for missing_values with a window of 4 to help me identify any sudden spikes in missing data?"}],"resultDescription":"Returns two analytical reports for the supplied rows: (1) a trailing mean series showing the rolling average of the selected field (missing_values or total_values) over the specified window, and (2) adjacent row changes showing the difference between consecutive row values. Both reports are computed locally on the submitted data with no external lookups.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows submitted — exceeds maximum limit","Invalid date format (not YYYY-MM-DD) — validation error","missing_values or total_values outside allowed numeric range — rejected","Window size outside 2–200 range — validation error","Null or missing required fields (row_id, dataset_group, date) — schema validation failure"],"whenToPreferThis":"Choose this endpoint when you need lightweight, self-contained statistical analysis of null coverage records — specifically trailing mean series and adjacent row changes — without any external data lookups or predictions. It is ideal for data quality monitoring pipelines where you supply your own records and need two standard analytical views at very low cost ($0.01 USDC for up to 200 rows).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:10.215Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-trailing-mean-series-adjacent-row-changes-3b758dfb"}