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Data Collection Completeness — Numeric Row Ordering + Secondary-Measure Weighted Mean
x402
Data Collection Completeness — Numeric Row Ordering + Secondary-Measure 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 2026-11-08).
Computes numeric row ordering and secondary-measure weighted mean analytics for data collection completeness records (observed vs expected values), producing 2 reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data collection completeness — Numeric row ordering + Secondary-measure weighted mean: Numeric row ordering + Secondary-measure weighted mean for supplied data collection completeness records (observed_values, expected_values). 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 2 analytical reports: (1) a numeric row ordering of the submitted records ranked by the selected field, and (2) a secondary-measure weighted mean calculated across the rows using the complementary measure as weights — all computed locally on the supplied data without any external lookup or live data.
Example use cases
Education completeness audit by course group
“I've got completeness records for group-a and group-b across four dates in October 2026, with observed and expected submission counts. Can you rank those rows numerically and give me a weighted mean using expected_values as the secondary measure?”
Weighted mean for multi-date data collection
“Here are 10 rows of data collection completeness data for our online course program — each row has a date, course group, observed count, and expected count. Run the numeric row ordering and secondary-measure weighted mean reports using observed_values as the field.”
Spotting completeness gaps across course cohorts
“I need to analyze whether our data collection is hitting expected targets — I have up to 50 rows with observed and expected values per course group per day. Can you give me the numeric row ordering and weighted mean breakdown using expected_values so I can see where we're falling short?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-22-121?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both numeric row ordering and a secondary-measure weighted mean on data collection completeness records (observed vs expected) for up to 200 rows in a single call. It is ideal for education or training data quality workflows where you want two analytical perspectives in one cheap call without any external data dependency. Prefer alternatives if you need histograms, correlation, pivot tables, or more than 200 rows.
Side effects
- Exceeding 200 rows causes rejection — trim input to ≤200 rows
- Missing required fields (row_id, date, observed_values, expected_values) cause validation errors
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Null values in both observed_values and expected_values for a row may skew or break weighted mean calculation
- Invalid field enum value (not 'observed_values' or 'expected_values') causes error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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