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Dataset Partition Sizes — Numeric Distribution + IQR Outlier Flags
x402
Dataset Partition Sizes — Numeric Distribution + 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 2026-10-22).
Computes numeric distribution statistics and IQR-based outlier flags for dataset partition size metrics (row_count or file_mb) across up to 200 supplied records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset partition sizes — Numeric distribution + IQR outlier flags: Numeric distribution + IQR outlier flags 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 independent analytical reports: (1) a numeric distribution summary (min, max, mean, median, quartiles, std dev, etc.) and (2) IQR-based outlier flags identifying which records fall below Q1−1.5×IQR or above Q3+1.5×IQR for the selected field (row_count or file_mb), across up to 200 input rows.
Example use cases
ETL pipeline partition size audit
“I have 150 daily dataset partitions and I want to know which ones have suspiciously high or low row_count values — can you run the numeric distribution and IQR outlier detection on them?”
File size skew detection across dataset groups
“Check the distribution of file_mb values across these 80 dataset partitions split between group-a and group-b, and flag any that fall outside the IQR bounds as outliers.”
Data quality check before ingestion
“Before I ingest these 200 partition records into our warehouse, can you run the numeric distribution and IQR outlier report on the row_count field so I can catch any badly sized partitions?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-07-080?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected dataset partition records (row_count and/or file_mb) and need both a distributional summary and IQR outlier flags in a single call, without any external data lookup or live system access. Ideal for data engineers auditing ETL pipeline partition consistency, data quality workflows, or anomaly pre-screening before ingestion — especially when cost efficiency matters (two reports for $0.01 USDC, up to 200 rows).
Side effects
- Input array empty or missing — returns validation error
- More than 200 rows supplied — rejected at schema level
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Field value out of allowed numeric range — schema rejection
- Null values in selected field may reduce effective sample size for distribution
- row_id missing or exceeds 80 characters — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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