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Transport Ridership Data Quality Suite
x402
Transport Ridership Data Quality Suite 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 analytical reports on transport ridership records: record quality audit, exact row deduplication, and trailing mean series computation.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transport ridership — Record quality audit + Exact row deduplication + Trailing mean series: Record quality audit + Exact row deduplication + Trailing mean 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 independent analytical reports: (1) a record quality audit flagging nulls, out-of-range values, and format issues per row; (2) an exact row deduplication report identifying and grouping identical records; (3) a trailing mean series for the selected numeric field (passenger_count or service_count) using the specified window size — all computed locally from the supplied data, covering up to 200 rows.
Example use cases
Monthly ridership data cleanup before reporting
“I have 150 rows of monthly bus ridership data with passenger_count and service_count fields and I need you to audit them for record quality issues, deduplicate any exact repeated rows, and compute a trailing mean over a window of 5 for passenger_count so I can prepare my monthly report.”
Detect anomalies in regional transit dataset
“Can you run a quality audit and deduplication check on my regional transit ridership records — about 80 rows covering regions like 'downtown' and 'suburbs' with dates from 2024-01-01 to 2024-03-31 — and also give me a trailing mean series with window 4 for service_count so I can spot anomalies?”
Pre-analysis data validation for transit agency
“Before I run my ridership analysis, can you check this dataset of 60 rows for data quality issues, find and flag any exact duplicate records, and calculate a rolling average with window size 2 on passenger_count? The rows include row_id, region, date, passenger_count, and service_count fields.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-05-216?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical operations on transport ridership data (quality audit, deduplication, and trailing mean) in a single low-cost call. Ideal for preprocessing transit datasets of up to 200 rows before visualization or modeling. Prefer this over generic data tools when your data specifically includes passenger_count and service_count fields and you need all three reports simultaneously without any external lookups or predictions.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, region, date, passenger_count, or service_count) — schema validation failure
- Invalid date format not matching YYYY-MM-DD pattern — rejected
- Window size outside range 2–200 — validation error
- Empty rows array — minimum 1 item required
- Numeric values outside allowed range (-1e12 to 1e12) — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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