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Survey Participation — Numeric Row Ordering + Explicit Missing-Value Fill
x402
Survey Participation — Numeric Row Ordering + 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 2026-11-02).
Sorts survey participation rows numerically and fills missing respondent/invitation values using zero, mean, or median imputation across up to 200 records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Survey participation — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied survey participation records (respondents, invitations). 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 analytical reports: (1) the survey participation rows reordered numerically by row ID, and (2) the same dataset with missing values in the specified field (respondents or invitations) explicitly filled using the chosen method (zero, mean, or median). Both reports are computed locally without external lookups.
Example use cases
Clean course survey with missing respondents
“I've got survey data for three course groups where some respondent counts are null — please sort the rows numerically and fill those missing respondents values using the median across the dataset. Rows: row-1 (group-a, 2026-11-01, respondents=50, invitations=100), row-2 (group-b, 2026-11-02, respondents=null, invitations=80), row-3 (group-a, 2026-11-03, respondents=40, invitations=null).”
Fill missing invitations with zero imputation
“Can you take my survey participation records and order them by row ID numerically, then fill any missing invitation values with zero? I have rows: row-1 (group-a, 2026-09-01, respondents=20, invitations=null), row-2 (group-b, 2026-09-02, respondents=35, invitations=200), row-3 (group-c, 2026-09-03, respondents=null, invitations=150) — use zero fill on the invitations field.”
Prepare education survey data with mean fill
“I need to clean up my education survey participation dataset before analysis — sort the 5 rows numerically and impute any missing respondent counts using the mean. Rows: row-1 (cohort-x, 2026-08-01, respondents=100, invitations=500), row-2 (cohort-y, 2026-08-02, respondents=null, invitations=400), row-3 (cohort-x, 2026-08-03, respondents=120, invitations=450), row-4 (cohort-z, 2026-08-04, respondents=null, invitations=300), row-5 (cohort-y, 2026-08-05, respondents=90, invitations=350).”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-10-124?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have survey participation data (respondents and invitations per course group) with missing numeric values that need imputation and records that need to be sorted by row number — up to 200 rows. It is ideal for lightweight, local data-cleaning tasks in education or training survey contexts where no external data lookup or live prediction is needed. It provides two reports (ordering + fill) in a single $0.01 call.
Side effects
- More than 200 rows submitted — request exceeds maxItems limit
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Missing required fields (row_id, course_group, date) causes rejection
- Numeric values outside ±1,000,000,000,000 range rejected
- Invalid method enum value (not zero/mean/median) causes error
- Invalid field enum value (not respondents/invitations) causes error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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