{"uid":"cap_pZkyAUcTjFvrawJ_c_eWp","slug":"data-ingestion-batches-exact-row-deduplication-numeric-distribution-fe176cd8","name":"Data Ingestion Batches — Exact Row Deduplication + Numeric Distribution Analytics","description":"Data ingestion batches — Exact row deduplication + Numeric distribution: Exact row deduplication + Numeric distribution 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-01-039?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"}}},"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_tSLgMjod4bqyLPjNCjOfz","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 data ingestion batch records to produce two reports: exact duplicate row detection and numeric distribution statistics for received_rows or accepted_rows fields.","exampleAgentPrompt":"Check my ingestion batch records for exact duplicate rows and show me the numeric distribution of received_rows — here are my records: row-1 on 2026-10-01, group-a, received 10, accepted 1; row-2 on 2026-10-02, group-b, received 20, accepted 2; row-3 on 2026-10-01, group-a, received 10, accepted 1.","exampleUseCases":[{"title":"ETL pipeline data quality audit","prompt":"I have 150 daily ingestion batch records from my ETL pipeline — can you check them for exact duplicate rows and give me the numeric distribution of accepted_rows so I can see how acceptance rates are spread across batches?"},{"title":"Ingestion anomaly investigation","prompt":"My data team suspects some ingestion logs are being recorded twice — can you run exact row deduplication on these 80 batch records and also show me the distribution of received_rows so I can spot any anomalies?"},{"title":"Dataset group comparison via distribution","prompt":"I want to understand how received_rows are distributed across these 200 ingestion batch entries from our dataset groups — run both the deduplication check and numeric distribution report on the received_rows field."}],"resultDescription":"Returns two analytical reports: (1) an exact row deduplication report identifying duplicate records across the supplied batch entries, and (2) a numeric distribution report (e.g. min, max, mean, percentiles, histogram buckets) for the selected numeric field (received_rows or accepted_rows). No external data is fetched; all analysis is performed locally on the submitted rows.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) — validation error","Date field does not match YYYY-MM-DD format — schema validation failure","Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejection","Empty rows array (minItems: 1 not met) — validation error","Invalid field enum value (must be 'received_rows' or 'accepted_rows') — error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 data ingestion batch records and need both exact duplicate row detection AND numeric distribution statistics in a single low-cost call. It is purpose-built for ingestion pipeline QA and uses local analytical engines with no external lookups, making it fast, deterministic, and privacy-safe. Prefer this over general-purpose analytics tools when your data fits the ingestion batch schema (row_id, dataset_group, date, received_rows, accepted_rows) and you want both reports bundled at $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:27.661Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-exact-row-deduplication-numeric-distribution-fe176cd8"}