{"uid":"cap_ZEehD-O9CqmpDyYN7ih35","slug":"transaction-fee-observations-exact-row-deduplication-explicit-missing-aa282c94","name":"Transaction Fee Observations — Exact Row Deduplication + Explicit Missing-Value Fill","description":"Transaction fee observations — Exact row deduplication + Explicit missing-value fill: Exact row deduplication + Explicit missing-value fill for supplied transaction fee observations records (fee_units, transaction_count). 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-finance-03-054?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","fee_units","transaction_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"fee_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80},"transaction_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","fee_units":10,"instrument_group":"group-a","transaction_count":1},{"date":"2026-10-02","row_id":"row-2","fee_units":20,"instrument_group":"group-b","transaction_count":2},{"date":"2026-10-03","row_id":"row-3","fee_units":15,"instrument_group":"group-a","transaction_count":3},{"date":"2026-10-04","row_id":"row-4","fee_units":30,"instrument_group":"group-b","transaction_count":4}],"maxItems":200,"minItems":1},"field":{"enum":["fee_units","transaction_count"],"type":"string","default":"fee_units"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_JV4Vtj9EaLZNv4ML81SnY","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 duplicate rows and fills missing values in transaction fee observation records (fee_units, transaction_count) for up to 200 rows, producing 2 analytical reports.","exampleAgentPrompt":"Clean up my transaction fee dataset by removing exact duplicate rows and filling any missing fee_units values using median imputation — I have about 50 rows with fields like row_id, instrument_group, date, fee_units, and transaction_count.","exampleUseCases":[{"title":"Impute missing fee_units before reporting","prompt":"I have 120 transaction fee observation rows and some of the fee_units values are null — can you fill them in using median imputation and also strip out any exact duplicate rows before I run my report?"},{"title":"Clean broker transaction data for reconciliation","prompt":"Before I reconcile my broker fee data, can you deduplicate the records and fill any missing transaction_count values with zero? I'll send you the rows with row_id, instrument_group, date, fee_units, and transaction_count."},{"title":"Prepare fee dataset for downstream analytics","prompt":"I need to prep my fee observations dataset — about 80 rows — by deduplicating exact matches and filling gaps in fee_units using mean fill so it's ready for my analytics pipeline."}],"resultDescription":"Two analytical reports covering the supplied transaction fee observation rows: one showing exact duplicate rows that were removed, and one showing records with missing fee_units or transaction_count values filled in using the chosen method (zero, mean, or median). Up to 200 rows processed per call.","failureModes":["Input exceeds 200 rows — request rejected","Missing required fields (row_id, instrument_group, date) cause row-level errors","Invalid date format (not YYYY-MM-DD) rejected by schema","Numeric values outside ±1,000,000,000,000 range rejected","Invalid fill method enum value causes validation error","Empty rows array rejected (minItems: 1)"],"whenToPreferThis":"Choose this endpoint when you have up to 200 transaction fee observation rows that need both exact duplicate removal and missing-value imputation in a single pass. It is purpose-built for fee_units and transaction_count fields and supports zero, mean, and median fill strategies. Use it when you need two clean analytical reports without any external lookup, prediction, or live data enrichment — purely local, deterministic processing of your supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:33:55.484Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-exact-row-deduplication-explicit-missing-aa282c94"}