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Account Research Coverage – Two-Measure Correlation + Explicit Missing-Value Fill
x402
Account Research Coverage – 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 2026-10-15).
Computes Pearson correlation between researched_accounts and target_accounts, and fills missing values using zero, mean, or median imputation, across up to 200 account research coverage records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Account research coverage — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied account research coverage records (researched_accounts, target_accounts). 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 independent analytical reports: (1) a Pearson correlation report quantifying the linear relationship between researched_accounts and target_accounts across the submitted rows, and (2) an explicit missing-value fill report showing which rows had nulls and what imputed values (zero, mean, or median) were substituted — all computed locally on the supplied data, no external lookups.
Example use cases
Sales Coverage Gap Analysis
“I have 50 rows of account research coverage data across our enterprise and SMB groups from Q3 — can you correlate researched_accounts with target_accounts and fill any nulls using mean imputation? I want to understand whether our research activity tracks our target volume.”
Cleaning Incomplete CRM Export
“We exported account coverage records from our CRM and several rows have missing target_accounts values — can you fill those nulls using median and also run the two-measure correlation so I can see if the cleaned data shows a meaningful relationship?”
Monthly Coverage Benchmark Report
“For our monthly review, I need a correlation report between researched_accounts and target_accounts across 120 rows of daily account data for October, with zero imputation for any missing entries — can you produce both statistical reports?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-08-184?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw account research coverage records (researched_accounts, target_accounts) that need both statistical correlation analysis and missing-value imputation in a single call. It is ideal for B2B sales analysts and RevOps teams who need to clean and correlate account coverage data without standing up their own analytics pipeline. Prefer this over general-purpose statistics APIs when you need both reports bundled at low cost ($0.01 USDC for up to 200 rows) and the data is already structured to match the schema.
Side effects
- Fewer than 1 row submitted — request rejected
- More than 200 rows submitted — exceeds maximum batch size
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range (±1 trillion) — rejected
- All values for one measure are null — correlation cannot be computed
- Invalid method enum value (not zero/mean/median) — schema error
- Invalid field enum value (not researched_accounts/target_accounts) — schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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