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Hospital Capacity Adjacent Row Changes and IQR Outlier Flags
x402
Hospital Capacity Adjacent Row Changes and 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 2026-10-30).
Computes adjacent row-to-row changes and IQR-based outlier flags for supplied hospital capacity records (occupied_beds or available_beds) across up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Hospital capacity — Adjacent row changes + IQR outlier flags: Adjacent row changes + IQR outlier flags for supplied hospital capacity records (occupied_beds, available_beds). 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 per call: (1) adjacent row-to-row change values for each record in the supplied sequence for the selected field, and (2) IQR-based outlier flags indicating which rows fall outside the interquartile range bounds — all computed locally from the supplied data with no external lookup or prediction.
Example use cases
Detecting bed occupancy spikes in daily reports
“I have daily hospital records for two regions over the past week — can you run adjacent row change analysis and IQR outlier detection on occupied_beds so I can spot any sudden spikes or anomalous days?”
Auditing available bed data for reporting errors
“We're auditing our hospital capacity dataset for data entry errors. Can you check these 50 rows of available_beds figures for row-to-row jumps and IQR outliers so we can flag anything that looks wrong before we submit the report?”
Regional capacity monitoring across multiple hospitals
“I'm comparing bed availability across three hospital regions over the last month — run IQR outlier flagging and adjacent row changes on the available_beds column so I can see which dates and regions look statistically unusual.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-09-157?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a batch of hospital capacity records (up to 200 rows) and need both sequential change detection and statistical outlier flagging in a single low-cost call ($0.01 USDC for both reports). Ideal for data quality audits, anomaly detection in time-series bed data, and pre-reporting validation where no live data lookup or predictive modeling is needed.
Side effects
- Fewer than 1 row or more than 200 rows submitted returns a validation error
- Missing required fields (row_id, region, date, occupied_beds, available_beds) cause schema rejection
- Invalid date format (non-YYYY-MM-DD) triggers pattern validation failure
- Invalid field enum value (not occupied_beds or available_beds) causes rejection
- Null values in the selected numeric field may affect IQR computation or produce null deltas
- row_id exceeding 80 characters or missing causes validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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