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Business Event Participation — Date×Category Pivot + Missing-Value Fill
x402
Business Event Participation — 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 2026-10-16).
Pivots business event participation data (attendee_count or company_count) by date and company group, filling missing values via zero, mean, or median imputation — returns two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Business event participation — Date by category pivot + Explicit missing-value fill: Date by category pivot + Explicit missing-value fill for supplied business event participation records (attendee_count, company_count). 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 analytical reports derived from the supplied event participation rows: (1) a date×company_group pivot table for the selected field (attendee_count or company_count), and (2) the same dataset with missing values explicitly filled using the chosen method (zero, mean, or median). Up to 200 input rows are supported per call.
Example use cases
Conference attendance cross-tab by company group
“I have 150 rows of conference participation data with dates, company groups, and attendee counts — pivot them into a date-by-company-group table and fill any gaps using the median method so I can see attendance patterns clearly.”
Zero-fill missing company counts before reporting
“My event dataset has some null company_count values across different company groups and dates — can you pivot it by date and company group and fill the missing entries with zero so the report is complete?”
Mean-imputed attendance matrix for trend analysis
“Can you take these business event participation records and build a date-by-category pivot for attendee_count, using mean imputation for any missing cells? I need two clean summary reports from the 80 rows I'm providing.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-19-189?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to reshape business event participation records into a date×category pivot table and simultaneously impute missing numeric values — all in a single, cheap ($0.01 USDC) local analytical call requiring no external lookups. Prefer it over general-purpose data tools when your data fits the specific schema (row_id, company_group, date, attendee_count, company_count) and you want two bundled reports (pivot + filled dataset) in one request.
Side effects
- Input rows exceed 200 — request rejected or truncated
- Missing required fields (row_id, company_group, date, attendee_count, company_count) cause validation errors
- Invalid date format (not YYYY-MM-DD) fails pattern validation
- Numeric values outside ±1,000,000,000,000 range rejected
- Empty rows array (minItems:1 not satisfied) causes error
- Unrecognized field or method enum value causes schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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