Trading Journal Observations — Two-Measure Correlation + 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 2026-10-26).
Computes Pearson correlation between entry_price and exit_price and fills missing values in a chosen field using zero, mean, or median imputation for up to 200 trading journal rows.
Trading journal observations — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + 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.
Two analytical reports: (1) a Pearson correlation result between entry_price and exit_price across the supplied rows, and (2) a missing-value fill report showing which rows had nulls in the chosen field and what values were imputed using the selected method (zero, mean, or median). Both reports are computed locally on the supplied data with no external data fetched.
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-09-184?utm_source=zero.xyzChoose this endpoint when you have tabular trading journal data (up to 200 rows) and need both a correlation analysis between entry and exit prices AND a missing-value imputation in a single call at low cost ($0.01 USDC). It is best suited for offline/batch analytical passes on supplied data rather than live market data lookups or predictive modeling. Prefer this over general-purpose statistics tools when you want a bundled two-report output (correlation + fill) specific to trading journal schema.
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
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