{"uid":"cap_zfO4H0HMU30X5vV5QIxWF","slug":"join-coverage-analytics-category-frequencies-base-100-series-5bb46628","name":"Join Coverage Analytics: Category Frequencies + Base-100 Series","description":"Join coverage — Category frequencies + Base-100 series: Category frequencies + Base-100 series 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-09-105?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_ZyK-L1oISyff1T1MZ5Anx","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 category frequency distributions and a base-100 indexed time series for join coverage metrics (matched_rows, source_rows) across up to 200 supplied rows.","exampleAgentPrompt":"Can you run the category frequency and base-100 series analysis on my join coverage data? I have 4 rows: 2026-10-01 group-a had 10 matched and 1 source, 2026-10-02 group-b had 20 matched and 2 source, 2026-10-03 group-a had 15 matched and 3 source, 2026-10-04 group-b had 30 matched and 4 source — use matched_rows as the field and index from row 0.","exampleUseCases":[{"title":"ETL pipeline join quality audit","prompt":"I've got daily join coverage stats for two dataset groups over the past week — can you show me the category frequencies and a base-100 trend series for matched_rows, starting the index from the first row?"},{"title":"Source row distribution by group","prompt":"Run the category frequency and base-100 index reports on my source_rows data across groups A and B for October — I have 50 rows with dates, row IDs, and matched/source counts, and I want the index anchored to row 5."},{"title":"Data reconciliation coverage trending","prompt":"I'm auditing how well our datasets reconcile — can you analyze these 120 join coverage records and give me both the category frequency breakdown and a base-100 series for matched_rows so I can spot which groups are drifting?"}],"resultDescription":"Returns two independent analytical reports: (1) category frequency counts showing how matched_rows or source_rows values distribute across dataset_group categories, and (2) a base-100 indexed time series normalizing the selected field relative to the specified base row, enabling trend comparison across dates and groups.","failureModes":["Missing required fields (row_id, date, dataset_group, matched_rows, source_rows) cause validation errors","Date strings not matching YYYY-MM-DD pattern are rejected","Exceeding 200 rows returns an error","base_index out of range (0–199) is rejected","Null values in matched_rows or source_rows may affect computation accuracy","Payment failure via x402 protocol prevents processing"],"whenToPreferThis":"Choose this endpoint when you need dual analytical reports — category frequency distributions AND a base-100 indexed series — on join coverage data (matched_rows vs source_rows) in a single call. Ideal for data engineers auditing ETL pipeline join rates, reconciliation analysts comparing dataset completeness across groups over time, or anyone needing lightweight local analytics on up to 200 rows without live lookups or external dependencies. At $0.01 USDC for both reports simultaneously, it's cost-efficient for iterative pipeline monitoring.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:35.197Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-category-frequencies-base-100-series-5bb46628"}