{"uid":"cap_GaBJ3XXIu_L3RVXuE9W1C","slug":"join-coverage-analytics-base-100-series-date-by-category-pivot-0dac1a61","name":"Join Coverage Analytics: Base-100 Series + Date-by-Category Pivot","description":"Join coverage — Base-100 series + Date by category pivot: Base-100 series + 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-09-167?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_lNY-JpT8kXF2TnhkvX7tI","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 local analytical reports — a Base-100 indexed time series and a Date × Category pivot table — from supplied join coverage data (matched_rows, source_rows).","exampleAgentPrompt":"I have join coverage data for two dataset groups over four dates — can you run the Base-100 series and date-by-category pivot on matched_rows, using row index 0 as the base, for these records: group-a on 2026-10-01 with 10 matched and 1 source, group-b on 2026-10-02 with 20 matched and 2 source, group-a on 2026-10-03 with 15 matched and 3 source, group-b on 2026-10-04 with 30 matched and 4 source?","exampleUseCases":[{"title":"ETL pipeline join rate monitoring","prompt":"I've got daily join coverage records for two pipelines over the past week — can you index matched_rows to base-100 starting from the first row and also pivot them by date and pipeline group so I can see coverage trends at a glance?"},{"title":"Data quality regression analysis","prompt":"Our join coverage dropped last quarter — please run a base-100 series and a date-by-category pivot on source_rows for these 50 records across our three dataset groups so I can see where the regression started."},{"title":"Cross-dataset group coverage comparison","prompt":"I want to compare join coverage between group-a and group-b over the last month — can you generate the base-100 indexed series and the date-by-category pivot for matched_rows on my 80 rows of coverage data, with base index set to 0?"}],"resultDescription":"Returns two analytical reports computed locally from the supplied rows: (1) a Base-100 indexed time series normalizing the selected metric (matched_rows or source_rows) relative to the chosen base row index, and (2) a Date × dataset_group pivot table breaking down coverage values by date and category. No external lookups or predictions are made; all computation is performed on the provided data.","failureModes":["Fewer than 1 or more than 200 rows supplied — returns validation error","Invalid date format (non YYYY-MM-DD) on any row — schema rejection","base_index out of range (≥ number of rows supplied) — index error","Null values in matched_rows or source_rows may affect normalization calculations","Missing required fields (row_id, dataset_group, date) — schema validation failure","Non-numeric values where numbers expected — type coercion error"],"whenToPreferThis":"Choose this endpoint when you have pre-collected join coverage data (matched_rows, source_rows) and need both a normalized Base-100 trend series and a Date × Category pivot in a single call without sending data to an external analytics platform. Ideal for data engineers and pipeline operators who want lightweight, privacy-preserving local analytics on up to 200 rows for $0.01 USDC. Not suitable if you need live data fetching, predictive modeling, or more than 2 report types per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:44.548Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-base-100-series-date-by-category-pivot-0dac1a61"}