{"uid":"cap_LrU4Jx2hXUZQmhiysYSSA","slug":"null-coverage-analytics-daily-sum-series-date-by-category-pivot-35b9c28d","name":"Null Coverage Analytics: Daily Sum Series + Date by Category Pivot","description":"Null coverage — Daily sum series + Date by category pivot: Daily sum series + Date by category pivot 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-03-143?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_FDjLom29Zq7MZ7pvs9Cz6","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":"Generates two analytical reports from supplied null-coverage records: a daily sum time series and a date-by-category pivot table, for up to 200 rows.","exampleAgentPrompt":"Can you run a null coverage analysis on these 150 records — I need both a daily sum time series and a date-by-category pivot for the missing_values field, grouped by dataset_group and date?","exampleUseCases":[{"title":"Data quality audit by team","prompt":"I have 120 records from our ETL pipeline with row_id, dataset_group, date, missing_values, and total_values. Can you give me a daily sum series and a pivot of missing_values by date and group so I can see which teams have the worst data gaps?"},{"title":"Monthly null trend report","prompt":"Here are 200 rows of data coverage records for October — each has a date, dataset group, and missing/total value counts. Run the daily sum series and date-by-category pivot on total_values so I can track completeness trends across the month."},{"title":"Pre-migration data completeness check","prompt":"Before we migrate this dataset, I want to understand our null coverage. I've got 80 records with dates, groups, missing_values, and total_values — can you give me the daily aggregated sums and a category pivot so I know where to focus cleanup?"}],"resultDescription":"Two independent analytical reports: (1) a daily sum time series aggregating the selected field (missing_values or total_values) by date, and (2) a date-by-category pivot table breaking down the selected field by dataset_group and date. Both are computed locally from the supplied rows with no external data access, covering up to 200 input rows.","failureModes":["Fewer than 1 row supplied — returns validation error","More than 200 rows supplied — request rejected, exceeds row limit","Missing required fields (row_id, dataset_group, date, missing_values, total_values) on any row — validation failure","Invalid date format (must match YYYY-MM-DD pattern) — schema validation error","Field selector not one of 'missing_values' or 'total_values' — enum validation error","Null or out-of-range numeric values beyond ±1,000,000,000,000 — validation rejection"],"whenToPreferThis":"Choose this endpoint when you need two simultaneous analytical reports (daily time series + category pivot) on null/missing-value coverage data in a single low-cost call. Ideal for data quality audits, ETL monitoring, and completeness reporting where the data is already available locally and no live lookup or external enrichment is needed. Best when working with up to 200 rows across multiple dataset groups and dates.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:46:33.978Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-daily-sum-series-date-by-category-pivot-35b9c28d"}