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Transport Ridership Adjacent Row Changes + Missing Value Fill
x402
Transport Ridership Adjacent Row Changes + Missing Value Fill 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).
Computes adjacent row changes and fills missing values for transport ridership records (passenger_count, service_count) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transport ridership — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill 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 analytical reports: (1) an adjacent row changes report showing the delta between consecutive rows for the specified field, and (2) a missing value fill report with nulls replaced using the chosen method (zero, mean, or median) — applied to passenger_count or service_count across all supplied rows.
Example use cases
Daily bus ridership change tracking
“I have daily bus passenger counts for 3 regions over the last month — can you calculate the adjacent row changes in passenger_count and fill any nulls using median, so I can see where ridership jumped or dropped day-over-day?”
Transit service count gap filling
“My service_count column has some missing values in this 80-row dataset of weekly transit records. Can you fill those gaps using mean imputation and also show me the row-by-row changes in service_count?”
Multi-region ridership data cleanup
“Before I run my analysis, I need to clean this 150-row transport ridership CSV — fill nulls in passenger_count with zeros and compute how each row's passenger count changed from the one before it, broken out by region.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-05-162?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously compute sequential row deltas AND impute missing values in transport ridership data (passenger_count or service_count) in a single API call. Ideal for transit analysts cleaning and exploring time-series ridership datasets of up to 200 rows without needing external data sources, predictions, or live lookups. The bundled two-report output makes it cost-effective at $0.01 USDC per call.
Side effects
- Exceeds 200-row limit — request rejected
- Missing required fields (row_id, date, region) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — rejected
- Invalid method enum value (must be zero, mean, or median) — error
- Invalid field enum value (must be passenger_count or service_count) — error
- Numeric values outside allowed range (-1T to +1T) — validation failure
- Empty rows array — error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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