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Tutoring Sessions Data Quality: Exact Row Deduplication + IQR Outlier Flags
x402
Tutoring Sessions Data Quality: Exact Row Deduplication + IQR Outlier Flags 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).
Deduplicates exact rows and flags IQR-based outliers in tutoring session records (session_minutes or session_count) for up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tutoring sessions — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags 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 reports: (1) an exact row deduplication report identifying which rows are exact duplicates, and (2) an IQR outlier flag report marking rows where the selected numeric field (session_minutes or session_count) falls outside the interquartile range boundaries. No external lookups or predictions are made — all analysis is local and deterministic.
Example use cases
Pre-analysis tutoring data cleanup
“I have a batch of 150 tutoring session records and I need to find any exact duplicate rows and flag sessions where session_minutes looks like an outlier before I run my weekly report — can you run the deduplication and IQR check on this dataset?”
Course group session count audit
“Can you check these tutoring records for duplicate entries and flag any session_count values that are statistical outliers using IQR? I want to make sure there are no data entry errors before I present the numbers to the school board.”
Monthly data validation before reporting
“Before I aggregate our tutoring platform's monthly data, please deduplicate these session records and identify any rows where session_minutes is an IQR outlier — I've got about 80 rows across several course groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-16-049?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local data quality checks specifically on tutoring session records with session_minutes and session_count fields. It is ideal for pre-processing pipelines that need both deduplication and IQR outlier detection in a single call for up to 200 rows. Prefer this over general-purpose data tools when you want a bundled two-report output at low cost ($0.01 USDC) without any external data lookups or ML predictions.
Side effects
- Fewer than 1 row submitted returns validation error
- More than 200 rows submitted exceeds the row limit and is rejected
- Missing required fields (row_id, date, course_group, session_minutes, session_count) causes schema validation failure
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Invalid field enum value (not 'session_minutes' or 'session_count') causes error
- Insufficient USDC balance results in payment failure via x402 protocol
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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