{"uid":"cap_6E-HC5ZcDZ9NWOjLWvxrK","slug":"join-coverage-analytics-numeric-row-ordering-date-by-category-pivot-758de57b","name":"Join Coverage Analytics: Numeric Row Ordering + Date-by-Category Pivot","description":"Join coverage — Numeric row ordering + Date by category pivot: Numeric row ordering + Date by category pivot for supplied join coverage records (matched_rows, source_rows). 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-09-122?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","matched_rows","source_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"matched_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_rows":1,"matched_rows":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_rows":2,"matched_rows":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["matched_rows","source_rows"],"type":"string","default":"matched_rows"}}},"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_COqFCwi0dSRGGUcfuGa33","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 on join coverage data — numeric row ordering and a date-by-category pivot — for up to 200 supplied records of matched_rows and source_rows.","exampleAgentPrompt":"I have join coverage records for two dataset groups — group-a and group-b — with matched_rows and source_rows across October 2026. Can you run numeric row ordering and a date-by-category pivot on matched_rows for these 4 rows and give me both reports?","exampleUseCases":[{"title":"ETL pipeline coverage audit","prompt":"I need to audit our ETL pipeline joins for October. Here are 50 records with row_id, dataset_group, date, source_rows, and matched_rows. Run numeric row ordering and a date-by-category pivot on matched_rows so I can see which groups and dates have the worst coverage."},{"title":"Data quality reporting by category","prompt":"We have daily join coverage logs across three dataset groups for the past month — about 90 rows total with matched and source row counts. Can you generate a date-by-category pivot and numeric row ordering report on source_rows so I can spot where coverage drops?"},{"title":"Cross-dataset join completeness ranking","prompt":"I want to rank our 120 join coverage records by source_rows numerically and also pivot matched_rows by date and dataset_group. Here's the data — field should be matched_rows. Give me both analytical reports."}],"resultDescription":"Returns two analytical reports: (1) a numeric row ordering of the supplied join coverage records, and (2) a date-by-category pivot table showing the selected metric (matched_rows or source_rows) broken down by date and dataset_group. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors","Date values not matching YYYY-MM-DD pattern are rejected","Submitting more than 200 rows exceeds the maxItems limit","Empty rows array (minItems: 1 violated) returns an error","Invalid field enum value (not matched_rows or source_rows) causes rejection","Null numeric values may affect ordering and pivot completeness"],"whenToPreferThis":"Choose this endpoint when you have tabular join coverage data (matched_rows, source_rows) with date and category labels and need both a numeric ordering view and a date-by-category pivot in a single low-cost call. Ideal for data engineers auditing ETL pipelines, monitoring join completeness over time, or preparing coverage summaries by dataset group. Not suitable for live data lookups, predictive analytics, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:35.831Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-numeric-row-ordering-date-by-category-pivot-758de57b"}