{"uid":"cap_IoO5fa-9a8razXNxVBNDz","slug":"transaction-fee-observations-weighted-mean-missing-value-fill-f02f42fb","name":"Transaction Fee Observations — Weighted Mean & Missing-Value Fill","description":"Transaction fee observations — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + 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-03-187?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_I84vehX91fxewuT1cpuut","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 a transaction-count-weighted mean and fills missing values in supplied transaction fee observation records using a chosen imputation method.","exampleAgentPrompt":"I have up to 200 rows of transaction fee observations with fee_units and transaction_count — can you compute the transaction-count weighted mean for fee_units and fill any missing values using the median imputation method?","exampleUseCases":[{"title":"Impute missing fees before reporting","prompt":"I have a dataset of daily transaction fee records across two instrument groups — some fee_units entries are null. Can you fill in those missing values using the median method and give me back the cleaned data with weighted means?"},{"title":"Weighted fee analysis by instrument group","prompt":"Here are 150 rows of fee observations with fee_units and transaction_count fields. Compute the transaction-count weighted mean for fee_units across all rows, using zero-fill for any missing values."},{"title":"Pre-pipeline fee data cleanup","prompt":"Before I load these transaction fee records into my analytics pipeline, I need missing transaction_count values filled using the mean method and a weighted mean computed — can you run both reports on my 80-row dataset?"}],"resultDescription":"Returns two analytical reports: (1) a secondary-measure weighted mean of the target field (fee_units or transaction_count) weighted by the other measure, and (2) an explicit missing-value fill for any null entries using the chosen method (zero, mean, or median). Both reports are computed locally on the supplied data with no external lookups.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows submitted — exceeds row limit","Invalid date format (not YYYY-MM-DD) — schema validation error","Numeric values outside allowed range (±1,000,000,000,000) — schema rejection","All values for target field are null — weighted mean may be undefined","Unknown imputation method enum value — validation error","Missing required fields (row_id, instrument_group, date) — schema error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of transaction fee observations (with fee_units and transaction_count fields) and need both a weighted mean and missing-value imputation in a single low-cost call ($0.01 USDC for 2 reports). It is ideal for offline/batch analytical preprocessing of fee data without requiring a live data connection or external predictions. Prefer alternatives if you need real-time fee lookups, forecasting, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T00:35:28.651Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-weighted-mean-missing-value-fill-f02f42fb"}