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Transport Ridership — Record Quality Audit + String Normalisation + Daily Sum Series
x402
Transport Ridership — Record Quality Audit + String Normalisation + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Runs three local analytical reports on supplied transport ridership data: a record quality audit, string normalisation, and a daily sum time series for passenger or service counts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transport ridership — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series for supplied transport ridership records (passenger_count, service_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three reports returned together: (1) a record quality audit flagging missing values, out-of-range numbers, or malformed dates; (2) normalised string output for the region field; (3) a daily aggregated sum time series for either passenger_count or service_count, covering up to 200 input rows.
Example use cases
Transit data quality check before reporting
“I've got a batch of 120 ridership records with row_id, region, date, passenger_count, and service_count. Can you audit them for quality issues, normalise the region strings, and give me a daily sum series for passenger_count before I send this to the board?”
Daily service count aggregation for operations
“Can you take these 80 transit rows and produce a daily sum series for service_count, plus flag any record quality problems and normalise the region labels so they're consistent?”
Cleaning messy ridership export from legacy system
“I exported ridership data from our old system — 150 rows with some nulls and inconsistent region names. Please run a quality audit, normalise the strings, and give me the daily totals for passenger_count so I can see what we're working with.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-05-198?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three simultaneous local analytical reports on transport ridership data — quality audit, string normalisation, and daily sum series — in a single low-cost call. Ideal for pre-analysis data cleaning pipelines where you want to validate, clean, and aggregate ridership figures (passenger or service counts) without any external lookups or live data dependencies.
Side effects
- Exceeds 200 row limit — request rejected
- Missing required fields (row_id, region, date, passenger_count, service_count) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- Numeric values outside allowed range — validation error
- Empty rows array — minItems constraint violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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