{"uid":"cap_DdJ5skKD2-OOydRWgg7ER","slug":"join-coverage-analytics-category-frequencies-iqr-outlier-flags-04738cc4","name":"Join Coverage Analytics: Category Frequencies + IQR Outlier Flags","description":"Join coverage — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags 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-09-107?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_hep1mrJPMhj9bkTkQUH0A","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 frequencies and IQR-based outlier flags for join coverage records (matched_rows, source_rows) across up to 200 rows, producing 2 independent analytical reports.","exampleAgentPrompt":"Can you analyze my join coverage data and flag any IQR outliers in matched_rows? I have 4 records across two groups — group-a and group-b — with dates from 2026-10-01 to 2026-10-04, and I want both a category frequency report and the outlier flags.","exampleUseCases":[{"title":"ETL pipeline join quality audit","prompt":"I've got join coverage records from our nightly ETL runs — rows with matched_rows and source_rows across several dataset groups. Can you compute category frequencies by group and flag any IQR outliers in the matched_rows field so I can spot which runs had abnormal match rates?"},{"title":"Data warehouse coverage monitoring","prompt":"I need to check our data warehouse join coverage for the past week. Here are 150 records with dataset_group, date, matched_rows, and source_rows — can you give me a frequency breakdown by group and flag any source_rows values that are statistical outliers using IQR?"},{"title":"Pre-merge dataset join validation","prompt":"Before we merge these two datasets, I want to validate our join coverage. Can you take these 80 join coverage records and produce category frequencies plus IQR outlier flags on the matched_rows column so we can see if any groups are way off?"}],"resultDescription":"Returns two independent analytical reports: (1) category frequency counts broken down by dataset_group for the selected field, and (2) IQR-based outlier flags identifying records whose matched_rows or source_rows values fall outside the interquartile range, covering up to 200 input rows.","failureModes":["Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors","Fewer than 1 or more than 200 rows rejected by schema constraints","Null numeric values may reduce IQR computation accuracy","Invalid date format (non-YYYY-MM-DD) rejected by pattern validation","Payment failure via x402 protocol blocks request","Field enum value other than 'matched_rows' or 'source_rows' causes rejection"],"whenToPreferThis":"Choose this endpoint when you need fast, local statistical analysis of join coverage metrics — specifically category frequency distributions and IQR outlier detection — without sending data to external ML services or live lookup systems. Ideal for data engineers validating ETL join quality on batches up to 200 rows at low cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:33.857Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-category-frequencies-iqr-outlier-flags-04738cc4"}