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Dataset Partition Sizes IQR Outlier Flags and Two-Measure Correlation
x402
Dataset Partition Sizes IQR Outlier Flags and Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Analyzes dataset partition size records (row_count, file_mb) to produce IQR-based outlier flags and a two-measure correlation report for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset partition sizes — IQR outlier flags + Two-measure correlation: IQR outlier flags + Two-measure correlation for supplied dataset partition sizes records (row_count, file_mb). 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) IQR outlier flags per row indicating which partition records have row_count or file_mb values outside the interquartile range, and (2) a two-measure correlation analysis between row_count and file_mb. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Flag bloated partitions in data lake
“I have 150 partition records from our data lake with dates, group names, row counts, and file sizes in MB — flag any outliers using IQR on the row_count field and also tell me how correlated row_count and file_mb are across those partitions.”
Data quality check before pipeline run
“Before I kick off our ETL pipeline, can you check these 80 dataset partition records for IQR-based outliers on file_mb and run the two-measure correlation report so I can see if file size is tracking with row count like it should?”
Audit partition skew across dataset groups
“I've got partition size records for two dataset groups — group-a and group-b — with row counts and file sizes over several dates. Can you flag any IQR outliers on row_count and show me the correlation between row_count and file_mb across all the records?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-07-176?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined IQR outlier detection and two-measure correlation analysis on dataset partition size metrics (row_count and file_mb) in a single low-cost call. Ideal for data engineers doing partition health checks, data quality audits, or storage anomaly detection without needing external lookups, predictions, or real-time data. Best suited for batch sizes up to 200 rows where both outlier flagging and correlation insight are needed together.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, dataset_group, date, row_count, file_mb) cause validation errors
- Null or non-numeric values in row_count or file_mb may affect IQR and correlation computation
- Date strings not matching YYYY-MM-DD pattern cause schema validation failure
- Fewer than 4 rows may produce unreliable IQR statistics
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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