{"uid":"cap_z7d5p_xCcrDzYgO7IreOx","slug":"null-coverage-adjacent-row-changes-and-explicit-missing-value-fill-9264495a","name":"Null Coverage Adjacent Row Changes and Explicit Missing-Value Fill","description":"Null coverage — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill 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-03-162?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_WCSO3w_dkSJI9CqY5yUd6","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 null coverage data by computing adjacent row-to-row changes and filling missing values using zero, mean, or median imputation across up to 200 rows.","exampleAgentPrompt":"I have a null coverage dataset with up to 50 rows — each has a row_id, dataset_group, date, missing_values, and total_values — can you run two reports on it: one showing adjacent row-to-row changes and one filling the nulls in missing_values using median imputation?","exampleUseCases":[{"title":"Tracking null rate drift over time","prompt":"I have daily null coverage records for two dataset groups over the past month — can you compute the adjacent row changes in missing_values so I can see how my null rate is shifting day by day?"},{"title":"Imputing missing totals with mean fill","prompt":"Some of my total_values entries are null in my coverage dataset — can you fill them in using mean imputation across my 80 rows and also show me the adjacent row differences?"},{"title":"Zero-fill audit for pipeline QA","prompt":"I'm doing a data quality check on a pipeline and need to zero-fill any missing_values nulls in my 30-row null coverage report while also getting a change-over-time breakdown between adjacent rows."}],"resultDescription":"Returns two analytical reports: (1) an adjacent row changes report showing the delta in the selected field between consecutive rows, and (2) an explicit missing-value fill report where nulls in the chosen field are replaced using the specified method (zero, mean, or median). Both reports are computed locally without external lookups, covering up to 200 input rows.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, missing_values, total_values) cause validation errors","Invalid date format (not YYYY-MM-DD) causes schema rejection","Numeric values outside allowed range (-1e12 to 1e12) rejected","Invalid enum value for field or method parameter","Empty rows array (minItems:1 violated) causes error"],"whenToPreferThis":"Choose this endpoint when you need a combined null coverage analysis that simultaneously shows row-to-row changes and fills missing values in a single low-cost call ($0.01 USDC). Ideal for lightweight data quality pipelines where you want offline statistical imputation (zero, mean, or median) alongside temporal delta tracking without hitting external data sources or prediction APIs.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:57:57.988Z","isFirstParty":false,"canonicalSlug":"null-coverage-adjacent-row-changes-and-explicit-missing-value-fill-9264495a"}