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Account Research Coverage — Base-100 Series + Explicit Missing-Value Fill
x402
Account Research Coverage — Base-100 Series + 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).
Normalizes account research coverage time-series data to a base-100 index and fills missing values using zero, mean, or median strategies, producing two analytical reports from supplied data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Account research coverage — Base-100 series + Explicit missing-value fill: Base-100 series + 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
Two independent analytical reports: (1) a base-100 indexed time series for the selected field (researched_accounts or target_accounts) anchored at the specified base row, and (2) an explicit missing-value fill report using the chosen strategy (zero, mean, or median). Both reports are computed locally from the supplied rows with no external data sources.
Example use cases
Monthly coverage indexing across sales groups
“I have monthly account research data for three sales teams — alpha, beta, and gamma — from Jan to Jun 2026 with some null entries in the researched_accounts column. Can you index the researched_accounts to a base-100 series starting at row 0 and fill the missing values using median so I can compare team performance on a common scale?”
Pipeline target account gap analysis
“I've got daily target_accounts figures for two company groups over Q3 2026, but several rows have missing values. Can you run a base-100 normalization on the target_accounts field starting from the first row, and impute the missing entries using mean fill, then give me both reports?”
Quarterly research coverage audit with zero-fill
“Here's my quarterly account research coverage dataset — 50 rows across four business units with some gaps in researched_accounts. Please normalize it to a base-100 series anchored at row 0 and fill all missing values with zero so the reports are complete and consistent.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-08-169?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) that need both base-100 normalization and missing-value imputation in a single call. It is ideal for sales ops or CRM analytics workflows where you want to compare time-series data across company groups on a common index without any live lookups or external enrichment. Prefer this over generic stats tools when you need both reports delivered together cheaply at $0.01 USDC per call.
Side effects
- Fewer than 1 or more than 200 rows submitted — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- base_index value exceeds the number of submitted rows — index out of bounds error
- All values in the selected field are null — mean/median fill may produce undefined results
- Non-numeric values passed for researched_accounts or target_accounts — type validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string | |
| base_index | integer |
Tags
x402
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