{"uid":"cap_clkVr02vTV8nJWbEGEo3P","slug":"trading-journal-observations-string-normalisation-missing-value-fill-c774bda4","name":"Trading Journal Observations — String Normalisation & Missing-Value Fill","description":"Trading journal observations — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied trading journal observations records (entry_price, exit_price). 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-09-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","entry_price","exit_price"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"exit_price":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"entry_price":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","exit_price":1,"entry_price":10,"instrument_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","exit_price":2,"entry_price":20,"instrument_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","exit_price":3,"entry_price":15,"instrument_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","exit_price":4,"entry_price":30,"instrument_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["entry_price","exit_price"],"type":"string","default":"entry_price"},"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_RnmV97-SWuugN_W7uw3qb","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 entry_price or exit_price values in trading journal observation records using zero, mean, or median imputation.","exampleAgentPrompt":"I have 50 trading journal rows with some null exit_price values — can you clean them up using median imputation and also normalise the string fields like instrument_group and date?","exampleUseCases":[{"title":"Fix null exit prices in trade log","prompt":"I've got a batch of 80 trade records and about a dozen of them are missing exit_price — can you fill those nulls using the median of the existing exit prices and normalise the string columns at the same time?"},{"title":"Zero-fill missing entry prices before backtesting","prompt":"Before I run my backtest, I need to fill any missing entry_price values with zero and clean up the string fields in my 120-row trading journal dataset — can you run that for me?"},{"title":"Mean imputation for incomplete trade data audit","prompt":"I'm auditing my trading journal and need a report showing how the entry_price column looks after filling in the missing values using the mean, along with string normalisation on all my instrument_group labels — I have about 150 rows."}],"resultDescription":"Returns two analytical reports per call: one covering string normalisation results (standardised instrument_group, date, and row_id fields) and one covering explicit missing-value fill results for the specified price field (entry_price or exit_price) using the chosen method (zero, mean, or median). Covers up to 200 input rows. No external data is fetched; all analysis is performed locally on the supplied data.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, date, instrument_group) on any row — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Numeric values out of allowed range (±1 trillion) — schema rejection","Invalid enum value for field or method parameters — request error","Empty rows array — minItems constraint violation"],"whenToPreferThis":"Choose this endpoint when you need a cost-effective ($0.01 USDC for 2 reports) local data cleaning pass on trading journal records — specifically when you need both string normalisation and missing-value imputation (zero, mean, or median) on entry_price or exit_price fields in a single call. It is best for offline data preparation of up to 200 rows with no need for live market data, external lookups, or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T00:35:36.267Z","isFirstParty":false,"canonicalSlug":"trading-journal-observations-string-normalisation-missing-value-fill-c774bda4"}