{"uid":"cap_ApsBi-w4GZdm1S-ZGh6Z-","slug":"join-coverage-analytics-exact-row-deduplication-iqr-outlier-flags-5ce8644d","name":"Join Coverage Analytics — Exact Row Deduplication + IQR Outlier Flags","description":"Join coverage — Exact row deduplication + IQR outlier flags: Exact row deduplication + 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-09-049?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_JsOWSM0NTxIc7wsEs0gnP","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":"Deduplicates exact rows and flags IQR-based outliers in join coverage data (matched_rows, source_rows) for up to 200 records, producing 2 independent analytical reports.","exampleAgentPrompt":"Can you run deduplication and IQR outlier detection on my join coverage data? I have rows with matched_rows and source_rows for groups like 'group-a' and 'group-b' across October 2026 — flag any duplicates and statistical outliers in the matched_rows field.","exampleUseCases":[{"title":"ETL pipeline data quality check","prompt":"I just ran a join between two datasets and got back these coverage records — can you deduplicate them and flag any outliers in the matched_rows counts using IQR? Here are 50 rows with row_id, dataset_group, date, source_rows, and matched_rows."},{"title":"Anomaly detection in source row counts","prompt":"Check my join coverage export for outliers — I want IQR-based flags on the source_rows field and exact duplicates removed. I have about 120 rows covering multiple dataset groups from January through March 2025."},{"title":"Dataset join audit before reporting","prompt":"Before I finalize my join coverage report, can you deduplicate my records and highlight any matched_rows values that look statistically abnormal? I have 80 rows grouped by dataset_group with dates in Q4 2024."}],"resultDescription":"Two independent analytical reports: (1) an exact row deduplication report identifying and removing duplicate records from the supplied join coverage rows, and (2) an IQR outlier flag report marking records whose selected field (matched_rows or source_rows) falls outside the interquartile range, indicating statistical anomalies. No external data is fetched; all analysis is performed on the supplied rows only.","failureModes":["Fewer than 1 row submitted — violates minItems constraint","More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) — validation error","Invalid date format (not YYYY-MM-DD pattern) — schema rejection","Null values for both matched_rows and source_rows may reduce outlier detection quality","Invalid field selector value (not 'matched_rows' or 'source_rows') — enum validation failure","Payment not completed — x402 payment required before response"],"whenToPreferThis":"Choose this endpoint when you need fast, local statistical analysis on join coverage datasets without any external lookups or predictions — specifically when you want both exact duplicate removal and IQR-based outlier flagging in a single call for up to 200 rows. It is ideal for data quality pipelines validating ETL join results, pre-reporting audits, or any workflow where matched_rows and source_rows counts need sanity checking. Prefer it over general-purpose analytics tools when the data is already structured in the expected join coverage schema and cost efficiency matters ($0.01 USDC for 2 reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:34.860Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-exact-row-deduplication-iqr-outlier-flags-5ce8644d"}