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Tutoring Sessions Record Quality Audit + Explicit Missing-Value Fill
x402
Tutoring Sessions Record Quality Audit + 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).
Audits tutoring session records for data quality issues and fills missing values in session_minutes or session_count fields using zero, mean, or median imputation — up to 200 rows, two reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tutoring sessions — Record quality audit + Explicit missing-value fill: Record quality audit + Explicit missing-value fill for supplied tutoring sessions records (session_minutes, session_count). 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 independent reports: (1) a record quality audit identifying issues such as nulls, out-of-range values, and malformed dates across the submitted rows; and (2) a missing-value fill report showing which rows had null values in the specified field (session_minutes or session_count) and what imputed values (zero, mean, or median) were substituted. All processing is done locally with no external lookups.
Example use cases
Pre-analysis data cleaning for tutoring logs
“I have 120 rows of tutoring session records with some nulls in session_minutes — can you audit the data quality and fill those missing values using median imputation before I run my analysis?”
Zero-filling missing session counts by group
“My tutoring dataset has missing session_count values across several course groups. Can you do a quality audit and fill all the nulls with zero so I can get a clean count summary?”
Mean imputation for incomplete session duration data
“I've got about 80 tutoring session rows where session_minutes is sometimes blank. Can you check the overall record quality and replace the missing minutes with the mean value across all rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-16-019?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and missing-value imputation for tutoring session records (session_minutes, session_count) in a single call. It is ideal for preprocessing education datasets before downstream analytics, dashboards, or reporting pipelines. Prefer this over generic data cleaning tools when your data specifically follows the tutoring session schema (row_id, course_group, date, session_minutes, session_count) and you want two structured reports — audit + fill — without any external API calls or live predictions.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes row-level validation failure
- Missing required fields (row_id, course_group, date) causes schema rejection
- Invalid method enum value (not zero/mean/median) causes request failure
- Invalid field enum value (not session_minutes/session_count) causes request failure
- Empty rows array causes rejection due to minItems:1 constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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