{"uid":"cap_0YNwlbc_CyllErrgMVG1L","slug":"null-coverage-grouped-numeric-summary-explicit-missing-value-fill-262cdddc","name":"Null Coverage Grouped Numeric Summary + Explicit Missing-Value Fill","description":"Null coverage — Grouped numeric summary + Explicit missing-value fill: Grouped numeric summary + 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-03-099?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_DDBlBmQ5xjSx7grOpOZr1","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 grouped numeric summaries and fills missing values (zero/mean/median) for null coverage records across up to 200 rows, delivering two analytical reports per call.","exampleAgentPrompt":"I have 4 rows of null coverage data across two groups — group-a and group-b — with missing_values and total_values recorded for each day from 2026-10-01 to 2026-10-04. Can you run a grouped numeric summary and fill any missing values using median imputation on the missing_values field?","exampleUseCases":[{"title":"Data completeness audit by team","prompt":"I have 150 rows of null coverage records for our data pipelines, split across 5 dataset groups with dates in October 2026. Can you give me a grouped numeric summary of missing_values and total_values per group, and fill any nulls using mean imputation?"},{"title":"Impute missing totals before reporting","prompt":"Before I send the monthly data quality report, can you fill all null entries in the total_values field using zero-fill across my 80 rows of null coverage data, grouped by dataset_group?"},{"title":"Compare null rates across product groups","prompt":"I have null coverage data for two product lines — group-a and group-b — recorded daily over 200 rows. Can you summarize the missing_values field numerically by group and impute any missing figures using median so I can compare completeness rates?"}],"resultDescription":"Returns two analytical reports per call: (1) a grouped numeric summary of the specified field (missing_values or total_values) aggregated by dataset_group, and (2) the same dataset with null/missing values explicitly filled using the chosen method (zero, mean, or median). All processing is performed locally on supplied data with no external lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, dataset_group, date, missing_values, total_values) cause validation errors","Invalid date format (not YYYY-MM-DD) causes schema rejection","Unknown fill method value outside zero/mean/median enum causes error","Empty rows array (minItems:1 violated) returns error","Numeric values outside ±1,000,000,000,000 range rejected"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of null coverage data (missing_values, total_values) and need both a grouped numeric summary by dataset_group AND explicit missing-value imputation (zero, mean, or median) in a single $0.01 USDC call. Prefer it over general-purpose analytics tools when you want two bundled offline reports — no external data fetching, no prediction, just deterministic computation on your supplied records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T06:53:48.649Z","isFirstParty":false,"canonicalSlug":"null-coverage-grouped-numeric-summary-explicit-missing-value-fill-262cdddc"}