{"uid":"cap_vjPOWSImLfwwD5LHmWBkH","slug":"join-coverage-analytics-adjacent-row-changes-date-by-category-pivot-8948be07","name":"Join Coverage Analytics: Adjacent Row Changes + Date-by-Category Pivot","description":"Join coverage — Adjacent row changes + Date by category pivot: Adjacent row changes + 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-09-160?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_fucpCBY0UnQEiD-kgknni","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":"Analyzes join coverage data (matched_rows, source_rows) across up to 200 rows, producing two reports: adjacent row-over-row change analysis and a date-by-category pivot table.","exampleAgentPrompt":"Can you analyze my join coverage data for the last week — I have matched_rows and source_rows across two groups, 'group-a' and 'group-b', for dates 2026-10-01 through 2026-10-04, and I want both the adjacent row-over-row changes and a pivot by date and category for the matched_rows field?","exampleUseCases":[{"title":"ETL pipeline join coverage audit","prompt":"I have daily join coverage stats for my ETL pipeline across two dataset groups — 'raw_events' and 'enriched_events' — from 2026-09-01 to 2026-09-30, with matched_rows and source_rows for each day. Can you run the adjacent row changes analysis and the date-by-category pivot on matched_rows so I can spot where coverage dropped?"},{"title":"Data quality monitoring by group","prompt":"I want to monitor source_rows across my dataset groups 'customers' and 'orders' over the past two weeks. Can you give me the row-over-row changes and a pivot table by date and group for the source_rows field?"},{"title":"Ad-hoc join coverage comparison across categories","prompt":"Here are 50 records of join coverage data across four dataset groups — 'pageviews', 'sessions', 'conversions', and 'signups' — each with a date, matched_rows, and source_rows. Run the adjacent row changes and the date-by-category pivot for matched_rows so I can compare how each group tracks over time."}],"resultDescription":"Returns two independent analytical reports computed locally on the supplied data: (1) an adjacent row changes report showing how matched_rows or source_rows shift between consecutive records, and (2) a date-by-category pivot table summarizing the chosen metric across dataset groups and dates. No external lookups or predictions are made; all analysis is based solely on the input rows provided (up to 200 rows).","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, date, dataset_group, matched_rows, source_rows) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Null values in numeric fields may affect adjacent row change calculations","field enum value not one of 'matched_rows' or 'source_rows' — validation error","Empty rows array — no analysis possible"],"whenToPreferThis":"Choose this endpoint when you have pre-collected join coverage tabular data (matched_rows and source_rows per date and dataset group) and need two specific analytical views — row-over-row change detection and a date-by-category pivot — without any external data lookup, prediction, or live monitoring. It is ideal for ad-hoc, offline analysis of up to 200 records at a very low cost ($0.01 USDC for both reports). Prefer alternatives if you need more than 200 rows, live data ingestion, or different analytical transformations such as time-series forecasting or anomaly detection.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:44.262Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-adjacent-row-changes-date-by-category-pivot-8948be07"}