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Trading Journal Observations — String Normalisation & Missing-Value Fill
x402
Trading Journal Observations — String Normalisation & Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).
Normalises string fields and fills missing entry_price or exit_price values in trading journal observation records using zero, mean, or median imputation.
Price / call$0.01
Success—
StatusUnknown
How this service works
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.
Output
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.
Example use cases
Fix null exit prices in trade log
“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?”
Zero-fill missing entry prices before backtesting
“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?”
Mean imputation for incomplete trade data audit
“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.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-09-037?utm_source=zero.xyzWhen to prefer
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.
Side effects
- 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
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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