{"uid":"cap_XKeqad6X7PUzpPgGPzdzT","slug":"transaction-fee-observations-daily-sum-series-explicit-missing-value-34a594dd","name":"Transaction Fee Observations — Daily Sum Series + Explicit Missing-Value Fill","description":"Transaction fee observations — Daily sum series + Explicit missing-value fill: Daily sum series + 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-03-145?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_t6enKSDxxd8UGi2-Y9B5F","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 daily sum time series and fills missing values for transaction fee observation records (fee_units, transaction_count) using a chosen fill method.","exampleAgentPrompt":"I have transaction fee records for a bunch of dates — can you compute the daily sum series for fee_units and fill any missing values using median imputation? Here are up to 200 rows with row_id, instrument_group, date, fee_units, and transaction_count fields.","exampleUseCases":[{"title":"Daily fee aggregation for reconciliation","prompt":"I have 150 transaction fee records across two instrument groups for October 2026 — can you sum up the fee_units by day and fill any missing daily values using the median? I need the daily totals for my month-end reconciliation."},{"title":"Transaction count gap-filling for reporting","prompt":"My transaction count time series has some null entries for certain dates — can you fill those missing transaction_count values using mean imputation and also give me the daily sum series across my instrument groups?"},{"title":"Fee analytics with zero-fill for missing days","prompt":"I've got about 80 rows of fee observation data with instrument_group, date, and fee_units. Can you build a daily sum series for fee_units and use zero-fill for any missing values so I can see a complete daily picture?"}],"resultDescription":"Two analytical reports: (1) a daily sum series aggregating the target field (fee_units or transaction_count) by date, and (2) the same dataset with explicit missing values filled using the chosen method (zero, mean, or median). Up to 200 input rows supported, processed using local analytical engines with no external lookups.","failureModes":["Input rows array is empty or exceeds 200 items — validation error","Date field does not match YYYY-MM-DD format — schema validation rejection","fee_units or transaction_count values outside allowed range (-1T to 1T) — rejected","Missing required fields (row_id, instrument_group, date) — request fails","Invalid fill method or field enum value — schema validation error","Payment of 0.01 USDC not completed — request not processed"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of transaction fee observation records and need both a daily sum aggregation and missing-value imputation in a single call. It is ideal for financial analysts who need to clean and summarize fee or transaction count time series data without setting up local infrastructure. Prefer this over general-purpose analytics tools when you want a lightweight, pay-per-use computation that handles two reports (daily sum + null fill) simultaneously for fee or count fields.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:32:56.366Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-daily-sum-series-explicit-missing-value-34a594dd"}