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Customer Segment Observations — Date×Category Pivot + Missing-Value Fill
x402
Customer Segment Observations — Date×Category Pivot + 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 2026-10-20).
Pivots customer segment observation rows by date and company group, then fills missing values using zero, mean, or median imputation, for account_count or revenue_amount fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — Date by category pivot + Explicit missing-value fill: Date by category pivot + Explicit missing-value fill for supplied customer segment observations records (account_count, revenue_amount). 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 up to 2 analytical reports: a date-by-category pivot table for the specified field (account_count or revenue_amount) with missing values explicitly filled using the chosen method (zero, mean, or median). The output is computed locally from the supplied rows with no external lookups.
Example use cases
Revenue pivot with zero fill
“I have monthly revenue_amount records for several customer groups with some missing entries — can you pivot them by date and company group, filling any gaps with zero?”
Account count matrix for reporting
“Take these customer segment rows and produce a date-by-company-group pivot table for account_count, filling missing cells with the mean value across each column.”
Segment gap analysis before modeling
“I need to clean up my segment observation dataset before feeding it into a model — pivot it by date and company_group for revenue_amount and impute any missing values using the median.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-189?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to reshape flat customer segment observation records into a date-by-category pivot table and handle missing values in a single step, especially when working with account_count or revenue_amount metrics across company groups. Ideal for pre-processing segment data before reporting or modeling when null imputation is required alongside pivoting.
Side effects
- Row count exceeds 200 limit — request rejected
- Invalid date format not matching YYYY-MM-DD pattern
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) in any row
- Invalid enum value for field or method parameters
- Empty rows array — no data to process
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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