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Sampling Observations IQR Outlier Flags + Keyed Dataset Comparison
x402
Sampling Observations IQR Outlier Flags + Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Runs two local analytical reports on sampling observation records: IQR-based outlier flagging and keyed dataset comparison, for up to 200 rows at $0.01 USDC.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — IQR outlier flags + Keyed dataset comparison: IQR outlier flags + Keyed dataset comparison for supplied sampling observations records (sample_value, sample_weight). 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) per-row IQR outlier flags indicating which rows fall outside the interquartile range for the selected field (sample_value or sample_weight), and (2) a keyed dataset comparison report showing row-by-row differences between the primary and secondary datasets matched on row_id and dataset_group. No external lookups or predictions are made; all analysis is performed locally on the supplied data.
Example use cases
Outlier detection in environmental samples
“I've got 150 rows of water quality sampling data with sample_value as the measured concentration and sample_weight as site volume — can you flag which rows are IQR outliers on sample_value and compare today's dataset against last week's baseline to see what changed?”
QC check on survey response data
“Run IQR outlier detection on my survey response scores (sample_value) and compare my current batch of 80 responses against the prior wave — I need to know which respondents look anomalous and where the two datasets diverge by row_id.”
Manufacturing batch sample validation
“I have two batches of production measurement readings — 120 rows each with batch ID as dataset_group, measurement date, sample_value as the reading, and sample_weight as unit count — please flag any IQR outliers in sample_value and show me the keyed comparison between the two batches.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-179?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both IQR-based outlier detection AND a keyed row-by-row dataset comparison on sampling observation data in a single low-cost call ($0.01 USDC for both reports). Ideal for data quality workflows where you want to validate a new batch of up to 200 sampling records against a reference dataset while simultaneously flagging statistical anomalies. Prefer this over general-purpose analytics APIs when working with structured sample_value/sample_weight records and needing reproducible, offline analytical results without external data lookups.
Side effects
- Exceeding 200-row limit returns a validation error
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) causes schema rejection
- Invalid date format (non-YYYY-MM-DD) triggers pattern validation failure
- Null values in sample_value or sample_weight may reduce outlier detection accuracy
- Mismatched row_ids between primary and secondary datasets result in unmatched rows in the comparison report
- Payment failure via x402 protocol prevents processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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