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Account Research Coverage: Numeric Distribution + Missing-Value Fill
x402
Account Research Coverage: Numeric Distribution + 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 2026-10-19).
Computes a numeric distribution report and fills missing values for account research coverage data (researched_accounts, target_accounts) across up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Account research coverage — Numeric distribution + Explicit missing-value fill: Numeric distribution + 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 numeric distribution report showing statistical spread (e.g. min, max, mean, median, percentiles) for the selected field across the supplied rows, and (2) an explicit missing-value fill report where null/missing values in the selected field have been replaced using the chosen method (zero, mean, or median). No external data is fetched; all computation is performed on the supplied rows only.
Example use cases
Sales coverage gap analysis by group
“I have account research records for group-a and group-b across October 2026 — can you run a numeric distribution report on researched_accounts and fill any nulls using the median, so I can see how evenly coverage is spread across groups?”
Zero-fill missing target account counts
“My dataset has some missing target_accounts values mixed in with valid numbers across 50 rows — please analyze the distribution of target_accounts and fill every missing value with zero so my downstream pipeline doesn't break.”
Mean imputation for monthly coverage review
“For our monthly review I need to clean up this account research table of about 120 rows — run a distribution report on researched_accounts and use mean imputation to fill in any gaps before I hand it off to the team.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-08-085?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of account research coverage data (researched_accounts and/or target_accounts) and need both a numeric distribution summary and explicit missing-value imputation in a single $0.01 call. It is ideal for lightweight, offline data cleaning and statistical summarization without requiring a full analytics platform. Prefer it over general-purpose analytics tools when you want a low-cost, deterministic, self-contained computation on supplied data with no external lookups.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows submitted — exceeds row limit
- Invalid date format (not YYYY-MM-DD) — validation error
- Missing required fields (row_id, company_group, date) — schema validation failure
- All values are null — mean/median imputation may be undefined
- Numeric values outside ±1 trillion range — rejected by schema
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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