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Transport Ridership String Normalisation + Category Frequencies
x402
Transport Ridership String Normalisation + Category Frequencies 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).
Normalises string fields and computes category frequencies across two measures (passenger_count, service_count) for up to 200 transport ridership records, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transport ridership — String normalisation + Category frequencies: String normalisation + Category frequencies 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 analytical reports for the submitted ridership rows: (1) a string normalisation report cleaning region and other text fields, and (2) a category frequency report showing how often each distinct value appears across passenger_count and service_count fields, covering up to 200 rows per call.
Example use cases
Regional ridership frequency summary
“I have 80 rows of daily bus ridership data with region, date, passenger_count, and service_count. Can you normalise the region name strings and give me a category frequency breakdown for both passenger counts and service counts?”
Data cleaning for transit dashboard
“Before I build my transit dashboard, I need to clean up these 120 ridership records — can you standardise the region strings and show me how frequently each category appears in the passenger_count and service_count columns?”
Multi-region transit pattern audit
“I'm auditing transit data across 15 regions for Q3. Can you run string normalisation and category frequency analysis on these 200 ridership rows so I can spot inconsistencies in how regions are labelled and see the distribution of passenger and service counts?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-05-024?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, offline string normalisation and categorical frequency analysis on small-to-medium transport ridership datasets (up to 200 rows) without requiring live data lookup, predictions, or external enrichment. It is ideal for data cleaning pipelines and exploratory analysis of transit records where you need both reports in a single low-cost call ($0.01 USDC).
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, region, date, passenger_count, service_count) cause row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside the allowed range (-1e12 to 1e12) fail schema validation
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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