{"uid":"cap_1slKCj6KY6-m91CjMUYSE","slug":"transaction-fee-observations-base-100-rebase-missing-value-fill-47e3c6eb","name":"Transaction Fee Observations — Base-100 Rebase + Missing Value Fill","description":"Transaction fee observations — Base-100 series + Explicit missing-value fill: Base-100 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-03-169?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_2_Xh7n60tDcbuZMgnXiBF","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":"Applies Base-100 index normalization and explicit missing-value imputation to user-supplied transaction fee observation records, returning two analytical reports.","exampleAgentPrompt":"I have a dataset of daily transaction fee observations with some missing values — can you rebase the fee_units column to a base-100 index starting at row 0 and fill any missing values using the median, for up to 200 rows grouped by instrument?","exampleUseCases":[{"title":"Normalize exchange fee trends over time","prompt":"I have 150 rows of daily fee data across two instrument groups with some nulls in fee_units — please rebase the series to base-100 starting from index 0 and fill the missing values using the mean, so I can compare fee trends across groups."},{"title":"Impute missing transaction counts for reporting","prompt":"My transaction count column has several null entries scattered through the dataset — can you fill those missing values using the median method and also give me the base-100 rebased series for transaction_count, using rows up to 200?"},{"title":"Prepare fee data for a month-over-month dashboard","prompt":"I need to clean up my October fee observation data — it has about 60 rows with some gaps — rebase fee_units to base-100 starting at the first row and impute any missing values with zero so I can drop it into my dashboard."}],"resultDescription":"Two analytical reports per call: (1) a Base-100 rebased series for the specified field (fee_units or transaction_count), indexed relative to the chosen base row; (2) an explicit missing-value-filled version of the same records using the selected imputation method (zero, mean, or median). Covers up to 200 input rows.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, instrument_group) cause validation errors","base_index out of range for the number of supplied rows","All values in the target field are null — mean/median imputation may be undefined","Malformed date strings not matching YYYY-MM-DD pattern fail validation","Fee or count values outside ±1,000,000,000,000 are rejected"],"whenToPreferThis":"Choose this endpoint when you have pre-collected transaction fee or count time series data and need both index normalization (Base-100 rebasing) and missing value imputation in a single low-cost call. Ideal for offline/batch analytical preparation of financial fee datasets before visualization or further modeling, where no live data lookup, prediction, or external action is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:32:32.571Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-base-100-rebase-missing-value-fill-47e3c6eb"}