{"uid":"cap_r2jsP9rwolMV4rMly4djb","slug":"transaction-fee-observations-category-frequencies-missing-value-fill-24b5d3c7","name":"Transaction Fee Observations — Category Frequencies + Missing-Value Fill","description":"Transaction fee observations — Category frequencies + Explicit missing-value fill: Category frequencies + 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-03-112?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_jnoiezgJNNEy9PrdKz2iM","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":"Analyzes up to 200 transaction fee observation records to produce category frequency counts and fill missing numeric values using zero, mean, or median imputation.","exampleAgentPrompt":"I have 50 transaction fee records with fields like fee_units, transaction_count, instrument_group, and date — can you run category frequency counts on them and fill any missing fee_units values using the median method?","exampleUseCases":[{"title":"Missing fee data imputation for trading logs","prompt":"I've got transaction fee logs with some null fee_units entries — can you fill those missing values using the median and also give me a frequency breakdown of each instrument_group? Here are up to 150 rows with row_id, date, fee_units, transaction_count, and instrument_group fields."},{"title":"Instrument group frequency audit","prompt":"Can you analyze my transaction fee dataset (about 80 rows) and tell me how frequently each instrument_group category appears, and also fill in any missing transaction_count values with zero?"},{"title":"Pre-pipeline fee data cleanup","prompt":"Before I load my fee observation data into our pipeline, I need two things: a count of how often each instrument_group shows up, and any missing fee_units replaced with the mean — I have around 120 rows to process."}],"resultDescription":"Two analytical reports: (1) a category frequency table showing how often each instrument_group value appears across the submitted rows, and (2) the same dataset with missing values in the specified numeric field (fee_units or transaction_count) filled using the chosen imputation method (zero, mean, or median). Up to 200 rows processed per call.","failureModes":["Fewer than 1 row submitted returns a validation error","More than 200 rows causes a rejection due to row limit","Invalid date format (not YYYY-MM-DD) fails schema validation","Numeric values outside ±1,000,000,000,000 are rejected","Missing required fields (row_id, instrument_group, date) cause row-level errors","Invalid method enum value (not zero/mean/median) fails validation","Invalid field enum value (not fee_units/transaction_count) fails validation"],"whenToPreferThis":"Choose this endpoint when you need both category frequency analysis and missing-value imputation on transaction fee data in a single call, without needing live data lookup, predictive modeling, or external integrations. Ideal for lightweight, local data-cleaning tasks on small-to-medium datasets (up to 200 rows) at low cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T06:47:19.250Z","isFirstParty":false,"canonicalSlug":"transaction-fee-observations-category-frequencies-missing-value-fill-24b5d3c7"}