{"uid":"cap_86TtL8elaUc0oPiwxGGVu","slug":"join-coverage-daily-sum-series-with-iqr-outlier-flags-fa7cde13","name":"Join Coverage Daily Sum Series with IQR Outlier Flags","description":"Join coverage — Daily sum series + IQR outlier flags: Daily sum series + 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-09-140?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_u6C5WkLO_yyPn-pL0XfQd","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 daily sum time series and IQR-based outlier flags for join coverage metrics (matched_rows, source_rows) from supplied row data","exampleAgentPrompt":"Can you analyze my join coverage data for the 'orders' dataset group — I have daily records from October 2026 with matched_rows and source_rows values — and give me a daily sum series plus flag any outlier days using IQR on the matched_rows field?","exampleUseCases":[{"title":"Detecting anomalous pipeline join days","prompt":"I have 30 days of join coverage records for my ETL pipeline with matched_rows and source_rows per day across two dataset groups — can you compute the daily sum series and flag any days where matched_rows looks like an outlier using IQR?"},{"title":"Monitoring source row ingestion trends","prompt":"Here are my daily source_rows counts across dataset groups for the past month — can you run a daily sum series and IQR outlier detection on source_rows so I can spot any days where ingestion was unusually high or low?"},{"title":"Auditing join quality across dataset groups","prompt":"I want to audit join coverage quality for my 'group-a' and 'group-b' datasets — I'll supply the matched_rows and source_rows by date, and I need a daily sum breakdown plus any IQR-flagged outlier dates highlighted in the report."}],"resultDescription":"Returns two analytical reports (one for each of the two included report slots): a daily sum time series aggregated from the supplied matched_rows or source_rows values, and an IQR-based outlier flag report identifying which rows or dates fall outside the interquartile range — all computed locally from the supplied data with no external lookups.","failureModes":["Missing required fields (row_id, date, dataset_group, matched_rows, source_rows) cause validation errors","Date values not matching YYYY-MM-DD pattern are rejected","Input arrays exceeding 200 rows are rejected","Null numeric values may affect IQR computation accuracy","Insufficient data points (e.g. fewer than 4 rows) may produce unreliable IQR statistics","Payment of 0.01 USDC required per call; missing payment results in 402 response"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of join coverage data (matched_rows and source_rows by date and dataset group) and need both a daily sum time series and IQR-based outlier flagging in a single low-cost call. It is ideal for data engineers and analysts who want lightweight, local statistical analysis of pipeline join quality without sending data to an external ML or prediction service. Prefer this over general analytics platforms when cost, simplicity, and offline computation are priorities.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T07:11:23.833Z","isFirstParty":false,"canonicalSlug":"join-coverage-daily-sum-series-with-iqr-outlier-flags-fa7cde13"}