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Survey Participation Data Quality Audit, String Normalisation & Weighted Mean
x402
Survey Participation Data Quality Audit, String Normalisation & Weighted Mean 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).
Runs three analytical reports on survey participation records: a record quality audit, string normalisation, and a secondary-measure weighted mean — all processed locally against supplied data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Survey participation — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean for supplied survey participation records (respondents, invitations). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three local analytical reports: (1) a record quality audit flagging malformed, missing, or out-of-range values per row; (2) normalised string output for the course_group field; (3) a weighted mean of the selected measure (respondents or invitations) across the supplied rows. All processing is done on the supplied data with no external lookups.
Example use cases
Education survey data cleanup
“I have a batch of 80 survey participation rows from our course groups — some dates might be malformed and group names are inconsistently cased. Can you run a quality audit, normalise the course_group strings, and give me the weighted mean for respondents?”
Invitation response rate analysis
“Run the three analytical reports on these 120 survey records — I want a quality audit of the rows, normalised course group labels, and a weighted mean computed on the invitations field.”
Pre-analysis data validation for survey team
“Before we hand this survey dataset off to the analytics team, can you do a record quality audit, clean up the string formatting in course_group, and calculate the weighted mean for respondents across all 35 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-10-205?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three specific analytical operations — quality auditing, string normalisation, and weighted mean computation — applied together to a batch of survey participation records (up to 200 rows) in a single low-cost API call. It is ideal for pre-processing educational survey data locally without any external data lookups or predictions.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, respondents, invitations, course_group) cause row-level errors
- Date strings not matching YYYY-MM-DD pattern will fail validation
- Null numeric values may be flagged in quality audit
- Payment of 0.01 USDC not provided causes 402 rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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