{"uid":"cap_UaWXlNDQ3cvvDqjCWnF-b","slug":"data-ingestion-batches-numeric-interval-filter-iqr-outlier-flags-f3e03396","name":"Data Ingestion Batches — Numeric Interval Filter + IQR Outlier Flags","description":"Data ingestion batches — Numeric interval filter + IQR outlier flags: Numeric interval filter + IQR outlier flags for supplied data ingestion batches records (received_rows, accepted_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-01-130?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","received_rows","accepted_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"accepted_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"received_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","accepted_rows":1,"dataset_group":"group-a","received_rows":10},{"date":"2026-10-02","row_id":"row-2","accepted_rows":2,"dataset_group":"group-b","received_rows":20},{"date":"2026-10-03","row_id":"row-3","accepted_rows":3,"dataset_group":"group-a","received_rows":15},{"date":"2026-10-04","row_id":"row-4","accepted_rows":4,"dataset_group":"group-b","received_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["received_rows","accepted_rows"],"type":"string","default":"received_rows"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_5u3eOiQQBN36da5ViDp82","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":"Applies a numeric interval filter and IQR-based outlier detection to up to 200 data ingestion batch records, returning two analytical reports on received_rows or accepted_rows.","exampleAgentPrompt":"Can you analyze my data ingestion batch records for outliers and range issues? I have 50 rows with received_rows and accepted_rows values — flag anything outside the interval 0 to 5000 using IQR outlier detection on the received_rows field.","exampleUseCases":[{"title":"ETL pipeline anomaly detection","prompt":"I've got 120 daily ingestion batch records with received_rows and accepted_rows values — can you flag any rows where received_rows falls outside the range 100 to 50000, and also highlight IQR outliers in that field so I can investigate my ETL pipeline?"},{"title":"Accepted rows quality audit","prompt":"Run an interval filter from 0 to 10000 and IQR outlier analysis on my accepted_rows column across these 80 ingestion batch records — I want to find any suspicious batch entries before I sign off on this month's data quality report."},{"title":"Multi-group ingestion batch review","prompt":"I have ingestion data split across two dataset groups, about 60 rows total. Can you check received_rows for values outside 500 to 20000 and flag the IQR outliers so I know which groups are behaving oddly?"}],"resultDescription":"Two analytical reports: one identifying rows whose selected numeric field (received_rows or accepted_rows) falls outside the specified minimum–maximum interval, and one flagging rows that are IQR-based statistical outliers — both derived locally from the supplied batch data with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — request rejected","Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) — validation error","Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure","Numeric values outside allowed range (±1,000,000,000,000) — rejected","Minimum greater than maximum threshold — may produce empty interval filter results","Null values in the target field — may reduce IQR computation accuracy","Payment not included or insufficient — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local statistical analysis of data ingestion batch records — specifically interval range filtering and IQR outlier flagging on received_rows or accepted_rows — without needing external data, predictions, or professional assessment. Ideal for data quality checks on small-to-medium ingestion logs (up to 200 rows) at very low cost ($0.01 for two reports). Prefer alternatives if you need more than 200 rows, different field types, time-series forecasting, or live pipeline monitoring.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T00:52:34.277Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-numeric-interval-filter-iqr-outlier-flags-f3e03396"}