{"uid":"cap_xj6LC-42uGPPIbNiXoAXR","slug":"null-coverage-analytics-adjacent-row-changes-two-measure-correlation-45497360","name":"Null Coverage Analytics: Adjacent Row Changes + Two-Measure Correlation","description":"Null coverage — Adjacent row changes + Two-measure correlation: Adjacent row changes + Two-measure correlation 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-03-158?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"}}},"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_2Q0XVI2uVOk4k8PyX387n","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 records by computing adjacent row changes and two-measure correlation across up to 200 rows of missing_values and total_values data.","exampleAgentPrompt":"Can you run two reports on my null coverage data — adjacent row changes and a two-measure correlation between missing_values and total_values — for these 4 records: group-a on 2026-10-01 had 10 missing out of 1 total, group-b on 2026-10-02 had 20 missing out of 2 total, group-a on 2026-10-03 had 15 missing out of 3 total, and group-b on 2026-10-04 had 30 missing out of 4 total?","exampleUseCases":[{"title":"Daily data pipeline quality audit","prompt":"I have 50 rows of daily pipeline data with missing_values and total_values per dataset group. Can you analyze how missing_values change between consecutive rows and also check whether missing_values and total_values are correlated across these records?"},{"title":"Detecting null spikes across dataset groups","prompt":"Run adjacent row changes and a two-measure correlation on my null coverage records for groups A and B from last quarter — I want to see if missing_values are spiking in specific rows and how strongly they track with total_values."},{"title":"Pre-release data completeness check","prompt":"Before we ship this dataset, can you compute adjacent row changes and the correlation between missing_values and total_values across these 120 records to make sure our null coverage looks stable and the two measures are behaving consistently?"}],"resultDescription":"Two analytical reports computed from the supplied rows: (1) an adjacent row changes report showing how the selected measure shifts between consecutive rows, and (2) a two-measure correlation report quantifying the statistical relationship between missing_values and total_values — all derived locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows supplied — request rejected","Missing required fields (row_id, date, dataset_group, missing_values, total_values) in any row — validation error","Date not matching YYYY-MM-DD format — schema validation failure","Null values in both measure fields making correlation undefined — degenerate result","Non-numeric values for missing_values or total_values — type error"],"whenToPreferThis":"Choose this endpoint when you need two specific analytical views — sequential row change detection and two-measure correlation — on null coverage data (missing_values, total_values) without any external data fetching or prediction. It is best for data quality auditing pipelines, pre-release completeness checks, or ongoing monitoring of dataset null rates, especially when you want both analyses bundled in a single low-cost call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:15.701Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-adjacent-row-changes-two-measure-correlation-45497360"}