{"uid":"cap_h_98MFQCirOtbyvyRHCa0","slug":"transaction-fee-observations-two-measure-correlation-explicit-missing-00347c66","name":"Transaction Fee Observations — Two-Measure Correlation + Explicit Missing-Value Fill","description":"Transaction fee observations — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + 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-03-184?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_rz8CIxdasvfPNapPwILIx","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":"Computes Pearson/Spearman correlation between fee_units and transaction_count, and fills missing values using zero, mean, or median imputation, for up to 200 rows of transaction fee data.","exampleAgentPrompt":"I have 50 rows of transaction fee observations with some nulls in fee_units — can you fill those missing values using median imputation and also compute the correlation between fee_units and transaction_count for me? Here's the data with row_id, instrument_group, date, fee_units, and transaction_count columns.","exampleUseCases":[{"title":"Fee-volume relationship analysis for trading desk","prompt":"I have 120 rows of daily fee and transaction count data across two instrument groups — can you compute the correlation between fee_units and transaction_count so I know if higher fees are associated with fewer trades?"},{"title":"Missing fee data cleanup before reporting","prompt":"My transaction dataset has about 30 null values in fee_units — can you fill those in using the mean of the non-null rows and give me back the cleaned records? I have up to 80 rows total with date, instrument_group, and transaction_count."},{"title":"Combined imputation and correlation for audit trail","prompt":"Before I send this fee dataset to auditors, I need to both fill missing transaction_count values using zero fill and generate a correlation report showing the relationship between fee_units and transaction_count — can you run both on my 150 rows?"}],"resultDescription":"Returns two analytical reports: (1) a correlation result quantifying the statistical relationship between fee_units and transaction_count across the supplied rows, and (2) a missing-value fill report where null entries in the specified field are replaced using the chosen method (zero, mean, or median), all computed locally on the supplied data with no external lookups.","failureModes":["Fewer than 1 row supplied — minimum row count not met","More than 200 rows submitted — exceeds maximum batch size","Invalid date format (must match YYYY-MM-DD pattern)","fee_units or transaction_count values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000)","Missing required fields (row_id, instrument_group, date) on any row","Invalid imputation method enum value (must be zero, mean, or median)","Payment failure or insufficient USDC balance for the $0.01 call"],"whenToPreferThis":"Choose this endpoint when you need both missing-value imputation and two-measure correlation computed together in a single $0.01 call on up to 200 rows of transaction fee data, without requiring any external data sources or live market lookups. It is ideal for pre-report data cleaning workflows, audit preparation, or exploratory analysis of fee-volume relationships where the data is already in hand.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T06:47:53.388Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-two-measure-correlation-explicit-missing-00347c66"}