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Training Assessments Base-100 Series + Explicit Missing-Value Fill
x402
Training Assessments Base-100 Series + 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 2026-10-26).
Analyzes training assessment pre/post scores by generating a base-100 indexed series and filling missing values using a chosen imputation method, producing two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training assessments — Base-100 series + Explicit missing-value fill: Base-100 series + Explicit missing-value fill for supplied training assessments records (pre_score, post_score). 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 base-100 indexed series of the chosen score field relative to the specified base row, and (2) the dataset with missing values explicitly filled using the chosen imputation method (zero, mean, or median). Both reports are computed locally from the supplied rows with no external lookups.
Example use cases
Employee training effectiveness baseline
“I've got 120 rows of employee pre and post training scores across three course groups, some post_scores are null. Index the post_score to a base-100 series starting from row 0 and fill the missing values with the mean — I need both reports.”
Course group score normalization
“Can you take my training assessment data for group-a and group-b — about 40 rows — and normalize the pre_score field to a base-100 index starting at row 5, using median to fill any missing scores? I want the two analytical outputs.”
Missing value audit before reporting
“Before I run my quarterly training report, I need to fill in missing pre_scores using zero imputation and also get a base-100 indexed series for those scores. I have 80 assessment rows across several course groups — can you run both reports?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-11-169?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to both normalize training assessment scores against a baseline index AND handle missing pre_score/post_score values in a single call, for datasets up to 200 rows. It is ideal for L&D analytics pipelines where raw assessment exports contain nulls and need standardized scoring before reporting. Prefer this over general statistics endpoints when your data is specifically structured as course-group training records with pre/post measurements.
Side effects
- Exceeding 200 rows returns an error or truncated result
- Invalid date format (not YYYY-MM-DD) causes validation failure
- Missing required fields (row_id, course_group, date) cause row rejection
- base_index out of range (0-199) returns an error
- Scores outside the numeric range trigger validation errors
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string | |
| base_index | integer |
Tags
x402
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