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Transport Ridership Numeric Interval Filter + Date by Category Pivot
x402
Transport Ridership Numeric Interval Filter + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).
Filters transport ridership rows by a numeric range on passenger_count or service_count, and generates a date-by-region pivot table — two analytical reports from user-supplied data, up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transport ridership — Numeric interval filter + Date by category pivot: Numeric interval filter + Date by category pivot 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
Returns two reports: (1) rows from the supplied dataset where the selected numeric field (passenger_count or service_count) falls within the specified minimum–maximum interval, and (2) a pivot table cross-tabulating that field's values by date and region/category. Both reports are computed locally on the supplied data with no external lookups.
Example use cases
Peak Hour Ridership Filtering
“I have daily bus ridership data for downtown and suburbs — filter it to rows where passenger_count is between 500 and 2000, and also show me how passenger counts break down by date and region in a pivot table. Here's my data: row-1 downtown 2026-09-01 passenger_count=1500 service_count=30, row-2 suburbs 2026-09-01 passenger_count=300 service_count=20, row-3 downtown 2026-09-02 passenger_count=1800 service_count=35.”
Low-Service Route Identification
“Can you run two reports on these transit records? First, filter to only routes where service_count is between 1 and 5 — I want to flag underserved routes. Also pivot the service_count by date and region so I can see patterns. Data: row-1 north 2026-10-01 passenger_count=50 service_count=2, row-2 south 2026-10-01 passenger_count=200 service_count=8, row-3 north 2026-10-02 passenger_count=40 service_count=3.”
Monthly Ridership Range Analysis
“I've got a month of ridership data across three regions and I need to know which records have passenger_count between 100 and 800, plus a date-by-region pivot of passenger_count so I can spot weekly patterns. Here's a sample: row-1 zone-a 2026-11-01 passenger_count=120 service_count=5, row-2 zone-b 2026-11-01 passenger_count=900 service_count=10, row-3 zone-c 2026-11-02 passenger_count=450 service_count=7.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-05-133?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of transport ridership data and need both a numeric range filter and a date-by-region pivot in a single call. It is ideal for local, offline-style analysis of supplied data without any live lookup, prediction, or external data enrichment. Prefer it over general-purpose analytics tools when you want a low-cost ($0.01 USDC), deterministic, two-report batch for transit datasets.
Side effects
- Missing required fields (row_id, region, date, passenger_count, service_count) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Submitting more than 200 rows exceeds the maximum and will be rejected
- Minimum greater than maximum produces an empty filter result
- Null values in the selected numeric field are excluded from interval filtering
- Payment of 0.01 USDC must be included; missing payment causes 402 error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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