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Water Monitoring IQR Outlier Flags
x402
Water Monitoring 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 2026-10-18).
Detects IQR-based statistical outliers in water monitoring records (litres consumed or cost) across sites and dates
Price / call$0.01
Success—
StatusUnknown
How this service works
Water monitoring - IQR outlier flags: IQR outlier flags for Water monitoring. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded iqr outlier flags deliverable.
Output
A row-level set of IQR outlier flags for each submitted water monitoring record, identifying which rows have values that fall outside the interquartile range bounds for the selected field (litres or cost), enabling downstream filtering, review, or data quality remediation.
Example use cases
Municipal water usage anomaly detection
“I have 120 daily water consumption readings across 6 municipal sites from January 2025. Can you run IQR outlier detection on the litres field and tell me which rows have anomalous values so I can investigate potential leaks or meter faults?”
Water cost audit for billing irregularities
“Here are 80 water billing records for our facilities across March and April 2025. Flag any cost entries that are IQR outliers — I want to catch any invoicing errors or unusual charges before we submit the budget report.”
Data quality screening before analytics pipeline
“Before I load this batch of 150 water monitoring records into our reporting dashboard, can you run IQR outlier flags on the litres field so I can exclude or review bad readings that might skew our site comparisons?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-analytics-water-monitoring-outliers?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local IQR-based statistical outlier detection on water monitoring records (up to 200 rows) without requiring external enrichment, forecasting, or ML models. It is purpose-built for the water sector with typed fields for site, date, litres, and cost, making it ideal for data quality screening, pre-pipeline validation, or operational anomaly triage on bounded datasets.
Side effects
- Empty or missing rows array returns validation error
- More than 200 rows submitted exceeds the maxItems limit and will be rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Null values in both litres and cost for the selected field may produce empty or degenerate IQR results
- Unknown field value other than 'litres' or 'cost' will fail enum validation
- Insufficient variance in data (all identical values) may yield no outlier flags
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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