{"uid":"cap_iwSOqukZ3s1F3vqopaEb7","slug":"savings-ledger-string-normalisation-explicit-missing-value-fill-a9c48651","name":"Savings Ledger — String Normalisation + Explicit Missing-Value Fill","description":"Savings ledger — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied savings ledger records (deposit_amount, withdrawal_amount). 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-23-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","deposit_amount","withdrawal_amount"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"deposit_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80},"withdrawal_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","deposit_amount":10,"instrument_group":"group-a","withdrawal_amount":1},{"date":"2026-10-02","row_id":"row-2","deposit_amount":20,"instrument_group":"group-b","withdrawal_amount":2},{"date":"2026-10-03","row_id":"row-3","deposit_amount":15,"instrument_group":"group-a","withdrawal_amount":3},{"date":"2026-10-04","row_id":"row-4","deposit_amount":30,"instrument_group":"group-b","withdrawal_amount":4}],"maxItems":200,"minItems":1},"field":{"enum":["deposit_amount","withdrawal_amount"],"type":"string","default":"deposit_amount"},"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_LIFJSXad3p4ga8JPJF31l","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 strings and fills missing values (zero, mean, or median) in savings ledger records containing deposit and withdrawal amounts, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have up to 200 rows of savings ledger records with deposit_amount and withdrawal_amount fields — some values are null. Can you normalise the strings and fill missing deposit_amount values using median imputation, then give me two analytical reports?","exampleUseCases":[{"title":"Clean savings export before analysis","prompt":"I've got a CSV export of my savings account with 150 rows — some deposit_amount entries are null and the instrument_group strings are inconsistent. Can you normalise the strings and fill the missing deposit_amount values using median so I can run my analysis cleanly?"},{"title":"Zero-fill missing withdrawals for reconciliation","prompt":"I'm reconciling my savings ledger and have about 80 rows where some withdrawal_amount fields are blank. Please fill those missing values with zero and normalise the string fields, then give me the two reports."},{"title":"Mean imputation for savings data pipeline","prompt":"My data pipeline ingests savings ledger rows and occasionally gets null deposit_amount values. For this batch of 120 rows, apply string normalisation and fill any missing deposit_amount entries using the mean — I need the two cleaned reports to pass downstream."}],"resultDescription":"Two analytical reports covering the processed savings ledger rows: one covering string normalisation results and one covering the explicit missing-value fill applied to the specified field (deposit_amount or withdrawal_amount) using the chosen method (zero, mean, or median). No external lookups or predictions are made; all processing uses local analytical engines.","failureModes":["Rows array empty or missing — validation error","More than 200 rows submitted — rejected with maxItems error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Unrecognised fill method or field enum value — schema rejection","Numeric values outside allowed range (±1,000,000,000,000) — validation error","Payment not provided or insufficient — x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you have savings ledger tabular data (deposit and withdrawal amounts with instrument groups and dates) that needs both string normalisation and missing-value imputation in a single pass, and you want two structured reports back without any live data lookup, prediction, or external action. Best suited for small-to-medium batches up to 200 rows where a low-cost ($0.01 USDC) local processing call is sufficient.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:38:13.566Z","isFirstParty":false,"canonicalSlug":"savings-ledger-string-normalisation-explicit-missing-value-fill-a9c48651"}