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Transport Ridership IQR Outlier Flags + Keyed Dataset Comparison
x402
Transport Ridership 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 2026-10-25).
Runs IQR-based outlier detection and keyed dataset comparison on up to 200 rows of transport ridership data (passenger_count or service_count), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transport ridership — IQR outlier flags + Keyed dataset comparison: IQR outlier flags + Keyed dataset comparison for supplied transport ridership records (passenger_count, service_count). 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
Two independent analytical reports: (1) IQR outlier flags identifying which row IDs fall outside the interquartile range for the selected field (passenger_count or service_count), including the computed IQR boundaries; (2) a keyed dataset comparison report showing row-by-row differences between the primary and secondary (other) dataset, matched by row_id.
Example use cases
Flagging anomalous daily ridership spikes
“I have 120 rows of daily bus ridership data with passenger_count and service_count by region — can you run IQR outlier detection on passenger_count and compare this week's data against last week's to see which row IDs changed significantly?”
Transit data quality audit before reporting
“Before I submit our monthly transit report, can you check these 80 ridership records for IQR-based outliers in service_count and compare them against the baseline dataset I'm providing to catch any keyed discrepancies?”
Comparing ridership across two route groups
“I've got two sets of ridership records — group-a and group-b routes, about 60 rows each — can you run an IQR outlier analysis on passenger_count and do a keyed comparison between the two datasets to see what's different?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-05-179?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have transport ridership tabular data (up to 200 rows) and need both IQR statistical outlier detection and a keyed row-by-row comparison against a reference dataset in a single $0.01 call. It is purpose-built for transit/ridership domain data with passenger_count and service_count fields. Prefer this over generic statistical APIs when you want two bundled reports — outlier flags and dataset diff — without live data lookup, prediction, or external integrations.
Side effects
- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — rejected with max items error
- Missing required fields (row_id, region, date, passenger_count, service_count) — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Numeric values outside allowed range (±1 trillion) — validation rejection
- row_id not matched between primary and other datasets — keyed comparison may return empty or partial results
- All values identical — IQR is zero, no outliers flagged
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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