{"uid":"cap_f1fUZmwtdI1MRHtP3e2AP","slug":"settlement-timing-string-normalisation-and-missing-value-fill-d524e338","name":"Settlement Timing String Normalisation and Missing-Value Fill","description":"Settlement timing — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied settlement timing records (settlement_minutes, payment_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-18-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","settlement_minutes","payment_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"payment_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80},"settlement_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","payment_count":1,"instrument_group":"group-a","settlement_minutes":10},{"date":"2026-10-02","row_id":"row-2","payment_count":2,"instrument_group":"group-b","settlement_minutes":20},{"date":"2026-10-03","row_id":"row-3","payment_count":3,"instrument_group":"group-a","settlement_minutes":15},{"date":"2026-10-04","row_id":"row-4","payment_count":4,"instrument_group":"group-b","settlement_minutes":30}],"maxItems":200,"minItems":1},"field":{"enum":["settlement_minutes","payment_count"],"type":"string","default":"settlement_minutes"},"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_Vsm8R1g4onn_zcO-d_D0G","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":"Normalises string fields and fills missing values in settlement timing records (settlement_minutes, payment_count) for up to 200 rows, returning 2 analytical reports.","exampleAgentPrompt":"Clean up my settlement timing data — I have 4 rows with instrument groups 'group-a' and 'group-b', some missing settlement_minutes values, and I want to fill those gaps using median imputation. Can you normalise the strings and fill the missing values?","exampleUseCases":[{"title":"Impute missing settlement minutes with median","prompt":"I have a batch of 50 settlement timing records where some settlement_minutes values are null — can you fill those missing values using the median of the existing data and normalise the string fields at the same time?"},{"title":"Zero-fill missing payment counts by group","prompt":"My payment_count column has several nulls across different instrument groups. Please fill those missing payment_count values with zero and clean up the string fields in the rows."},{"title":"Prepare settlement data for downstream reporting","prompt":"Before I hand off my settlement timing dataset to the reporting team, I need to normalise all string columns and use mean imputation to fill any gaps in the settlement_minutes field — can you process these 120 rows for me?"}],"resultDescription":"Two analytical reports covering the submitted settlement timing rows: one for string normalisation results and one for explicit missing-value fill outcomes, applied to the chosen field (settlement_minutes or payment_count) using the selected method (zero, mean, or median).","failureModes":["Input array exceeds 200 rows — request rejected","Missing required row fields (row_id, instrument_group, date, settlement_minutes, payment_count) — validation error","Invalid fill method value outside enum (zero, mean, median) — schema error","Invalid field value outside enum (settlement_minutes, payment_count) — schema error","Date not matching YYYY-MM-DD pattern — validation failure","Payment failure or insufficient USDC balance — transaction rejected"],"whenToPreferThis":"Choose this endpoint when you have raw settlement timing records with messy string fields or missing numeric values (settlement_minutes or payment_count) and need a quick, low-cost ($0.01 USDC) local analytical clean-up without live lookups, external data enrichment, or predictive modelling. It is ideal for pre-processing up to 200 rows before downstream reporting or analysis.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:32:44.967Z","isFirstParty":false,"canonicalSlug":"settlement-timing-string-normalisation-and-missing-value-fill-d524e338"}