{"uid":"cap_nFt1ZE4wYy8oOcdnD9zNw","slug":"null-coverage-analytics-numeric-row-ordering-two-measure-correlation-24370a0d","name":"Null Coverage Analytics — Numeric Row Ordering + Two-Measure Correlation","description":"Null coverage — Numeric row ordering + Two-measure correlation: Numeric row ordering + 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-03-120?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_sy7XFk24YIiutd9cELgrT","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":"Runs two local analytical reports on null coverage data: numeric row ordering and two-measure correlation between missing_values and total_values, for up to 200 rows.","exampleAgentPrompt":"Can you run numeric row ordering and two-measure correlation reports on my null coverage data? I have 4 rows with fields row_id, dataset_group, date, missing_values, and total_values — for example row-1 in group-a on 2026-10-01 had 10 missing out of 1 total, row-2 in group-b on 2026-10-02 had 20 missing out of 2 total — and I want to analyze the missing_values field.","exampleUseCases":[{"title":"Data pipeline completeness audit","prompt":"I have records from my ETL pipeline showing missing_values and total_values per dataset group and date — can you run numeric row ordering and correlation analysis on them so I can see which groups have the worst null coverage patterns?"},{"title":"Time-series null trend correlation","prompt":"I've got about 50 rows of daily null coverage stats across two dataset groups, each with a date, missing_values, and total_values. Can you compute how missing_values and total_values correlate and rank the rows numerically by missing_values?"},{"title":"Data quality report for multiple groups","prompt":"My data team collected null coverage metrics — row IDs, groups, dates, missing counts, and total counts — for 120 records. Can you run both the numeric ordering and two-measure correlation reports on the total_values field so we can benchmark completeness across groups?"}],"resultDescription":"Returns two analytical reports computed locally: (1) a numeric row ordering report ranking the supplied rows by the selected measure (missing_values or total_values), and (2) a two-measure correlation report showing the statistical relationship between missing_values and total_values across the supplied rows. No external lookups or predictions are made.","failureModes":["Fewer than 1 row provided — minimum input requirement not met","More than 200 rows submitted — exceeds maximum row limit","Missing required fields (row_id, dataset_group, date, missing_values, total_values) on any row","Date field not matching YYYY-MM-DD pattern — validation error","Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejected","Invalid field enum value (must be 'missing_values' or 'total_values')","Payment not processed — x402 payment required at $0.01 USDC"],"whenToPreferThis":"Choose this endpoint when you need two simultaneous analytical reports — numeric row ordering and two-measure correlation — on null coverage records with missing_values and total_values fields. Ideal for data quality workflows where you want to understand both the ranked order of rows by a completeness metric and how the two measures co-vary, all computed locally without external API calls or ML predictions. Best when your dataset is under 200 rows and you need a quick, cheap ($0.01 USDC) paired analytics result.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T12:51:32.134Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-numeric-row-ordering-two-measure-correlation-24370a0d"}