{"uid":"cap_s-dLcDKV1heRI8M1bJYH0","slug":"dataset-partition-sizes-duplicate-key-report-iqr-outlier-flags-cf7c0208","name":"Dataset Partition Sizes — Duplicate Key Report + IQR Outlier Flags","description":"Dataset partition sizes — Duplicate key report + IQR outlier flags: Duplicate key report + IQR outlier flags for supplied dataset partition sizes records (row_count, file_mb). 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-07-065?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","row_count","file_mb"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"file_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_count":{"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","file_mb":1,"row_count":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","file_mb":2,"row_count":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","file_mb":3,"row_count":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","file_mb":4,"row_count":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["row_count","file_mb"],"type":"string","default":"row_count"}}},"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_1rNKHpXX5qzokFZVky5Ow","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":"Analyzes up to 200 dataset partition size records to produce a duplicate key report and IQR-based outlier flags for row_count or file_mb fields.","exampleAgentPrompt":"Check my dataset partition records for duplicate row IDs and IQR outlier flags on the row_count field — here are my rows: row-1/group-a/2026-10-01 with 10 rows and 1MB, row-2/group-b/2026-10-02 with 20 rows and 2MB, row-3/group-a/2026-10-03 with 15 rows and 3MB, row-4/group-b/2026-10-04 with 30 rows and 4MB.","exampleUseCases":[{"title":"Data pipeline partition quality audit","prompt":"I have 50 partition records from our nightly ETL pipeline — each with a row_id, dataset_group, date, row_count, and file_mb. Can you run a duplicate key check and flag any IQR outliers on the row_count field so I can catch bad partitions before we load to the warehouse?"},{"title":"Storage anomaly detection in file sizes","prompt":"Can you analyze these dataset partition records for duplicate keys and flag any file_mb values that are IQR outliers? I want to spot partitions that are unusually large or small compared to the rest of the group."},{"title":"Pre-merge data integrity check","prompt":"Before I merge these 120 dataset partition records, check them for any duplicate row_id entries and flag which partitions have row_count values that fall outside the IQR range — I want to catch data quality issues early."}],"resultDescription":"Returns two independent analytical reports: (1) a duplicate key report identifying any repeated row_id values across the supplied partition records, and (2) IQR outlier flags marking records whose chosen metric (row_count or file_mb) falls outside the interquartile range. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — request rejected","Invalid date format (must match YYYY-MM-DD) — validation error","Missing required fields (row_id, dataset_group, date) — schema validation failure","Invalid field enum value (must be row_count or file_mb) — error response","Null numeric values may affect IQR computation if too many are null","Payment not included or insufficient — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local duplicate-key detection and IQR-based outlier flagging specifically for dataset partition size records (row_count and file_mb). It is ideal for data engineering workflows where you want a quick, cheap ($0.01 USDC) quality check on up to 200 partition records without sending data to a full analytics platform. Prefer this over general-purpose analytics APIs when you need both duplicate detection and statistical outlier flagging in a single call on structured partition metadata.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T07:19:40.830Z","isFirstParty":false,"canonicalSlug":"dataset-partition-sizes-duplicate-key-report-iqr-outlier-flags-cf7c0208"}