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Survey Participation Two-Measure Correlation and Missing-Value Fill
x402
Survey Participation Two-Measure Correlation and 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).
Computes Pearson correlation between respondents and invitations, and fills missing values using zero/mean/median imputation, for up to 200 survey participation records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Survey participation — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + 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) a Pearson correlation report quantifying the relationship between the two specified measures (respondents and invitations), and (2) a dataset with missing values in the chosen field filled using the selected imputation method (zero, mean, or median). Both reports are generated from the supplied rows without any external data lookups.
Example use cases
Education survey response rate analysis
“I have 150 rows of survey participation records across several course groups with dates, respondent counts, and invitation counts — some respondent values are null. Can you correlate respondents with invitations and fill those missing respondents using median imputation?”
Zero-fill missing invitations before reporting
“My survey dataset has about 80 rows with some null invitation values. Can you fill those missing invitations with zero and also give me the correlation between respondents and invitations across all rows?”
Course group participation correlation check
“I want to understand how well invitation volume predicts survey responses across our course groups. I have participation records for the last quarter — can you correlate the two measures and fill any missing respondent values using mean imputation?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-10-184?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have survey participation data (respondents and invitations) with up to 200 rows and need both a two-measure correlation analysis and missing-value imputation in a single low-cost call. Prefer it over general-purpose analytics when working specifically with course-group survey records and needing both reports bundled for $0.01 USDC. Not suitable for prediction, external data enrichment, or datasets larger than 200 rows.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, course_group, date, respondents, invitations) cause validation failure
- Invalid date format (non-YYYY-MM-DD) causes schema rejection
- Unsupported fill method enum value causes error
- All values in the target field are null, making mean/median imputation undefined
- Numeric values outside ±1,000,000,000,000 boundary cause validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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