Trading Journal Observations — Numeric Distribution + Explicit 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).
Analyzes up to 200 trading journal rows by computing numeric distribution statistics and filling missing values for entry_price and exit_price fields using zero, mean, or median imputation.
Trading journal observations — Numeric distribution + Explicit missing-value fill: Numeric distribution + 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.
Returns two analytical reports: (1) a numeric distribution summary (e.g. min, max, mean, median, percentiles, spread) for the specified price field across up to 200 rows, and (2) an explicit missing-value fill report showing which rows had null values and what imputed values were applied using the chosen method (zero, mean, or median). All computation is local with no external data lookups.
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-09-085?utm_source=zero.xyzChoose this endpoint when you have trading journal data with entry_price and exit_price columns and need both a statistical distribution summary and a missing-value imputation report in a single call for up to 200 rows. It is ideal for pre-processing trade logs before backtesting or strategy analysis when you want offline, deterministic computation with no external data dependencies. Prefer it over general-purpose analytics APIs when you specifically need the combination of distribution profiling and explicit null-fill for financial price fields.
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
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