{"uid":"cap_nyQokWxZ39GWFBkGNPvpf","slug":"null-coverage-analytics-numeric-distribution-two-measure-correlation-63c33a13","name":"Null Coverage Analytics: Numeric Distribution + Two-Measure Correlation","description":"Null coverage — Numeric distribution + Two-measure correlation: Numeric distribution + 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-03-081?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_oC_gPaf6bhZ6yVVX8GCfJ","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 numeric distribution statistics and two-measure correlation for null coverage records (missing_values, total_values) supplied by the caller — up to 200 rows, two independent reports.","exampleAgentPrompt":"Analyze the distribution of missing_values and also give me the correlation between missing_values and total_values for this null coverage dataset — I have 4 rows: row-1 (group-a, 2026-10-01, missing=10, total=1), row-2 (group-b, 2026-10-02, missing=20, total=2), row-3 (group-a, 2026-10-03, missing=15, total=3), row-4 (group-b, 2026-10-04, missing=30, total=4).","exampleUseCases":[{"title":"Data quality audit across pipeline batches","prompt":"I have 50 rows of null coverage data from our ingestion pipeline — each row has a row_id, dataset_group, date, missing_values, and total_values. Can you compute the numeric distribution of missing_values and give me the two-measure correlation between missing_values and total_values?"},{"title":"Completeness monitoring across dataset groups","prompt":"Here are 100 records from our weekly completeness check, grouped into 'finance' and 'ops'. For the field missing_values, give me the distribution stats and the correlation with total_values so I can see if larger datasets tend to have more nulls."},{"title":"Pre-model data quality summary","prompt":"Before we train, I need to understand our null coverage: I've got 80 rows with missing_values and total_values filled in per date. Run both the numeric distribution report and the two-measure correlation report on these rows using missing_values as the primary field."}],"resultDescription":"Returns two independent analytical reports: (1) a numeric distribution summary (e.g. min, max, mean, median, std dev, percentiles) for the selected field (missing_values or total_values) across up to 200 supplied rows, and (2) a two-measure correlation report between missing_values and total_values. No external lookups or predictions are made — all computation is local and deterministic.","failureModes":["Missing required fields (row_id, date, missing_values, total_values) cause validation errors","More than 200 rows supplied causes rejection or truncation","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Null or non-numeric values in missing_values/total_values may affect correlation computation","Empty rows array returns an error"],"whenToPreferThis":"Use this endpoint when you have pre-collected null coverage records (missing_values and total_values per row) and need both a numeric distribution and a two-measure correlation analysis in one call without any external data fetching or prediction. Ideal for data quality audits, pipeline monitoring, or pre-modeling completeness checks where you want two reports for up to 200 rows at minimal cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T06:55:17.453Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-numeric-distribution-two-measure-correlation-63c33a13"}