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Transport Ridership Base-100 Series & Missing-Value Fill
x402
Transport Ridership Base-100 Series & 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 a base-100 index series and fills missing values for transport ridership data (passenger_count or service_count) across up to 200 rows in two combined analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transport ridership — Base-100 series + Explicit missing-value fill: Base-100 series + 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
Returns two analytical reports for the supplied transport ridership dataset: (1) a base-100 index series where the specified base row equals 100 and all other rows are scaled relative to it, and (2) an explicit missing-value filled version of the chosen field (passenger_count or service_count) using the selected fill method (zero, mean, or median). Both reports use local analytical engines with no external data lookups.
Example use cases
Monthly ridership trend indexing
“I have 120 rows of monthly bus ridership data across 5 city regions from 2023 to 2024, some passenger_count values are null — can you normalize them to a base-100 series starting from row 0 and fill the missing values using median imputation?”
Service count baseline comparison
“Here are 80 records of daily train service counts by region with some gaps — please compute a base-100 index anchored at row 5 and fill the missing service_count entries with zero so I can compare service levels across regions.”
Pandemic recovery ridership analysis
“I've got 200 rows of weekly subway passenger data covering the pandemic period with a lot of nulls — run the base-100 normalization from the first row using mean fill on passenger_count so I can see the recovery trend clearly.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-05-169?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected transport ridership data (passenger counts or service counts) that needs to be normalized to a base-100 index for trend comparison and/or has missing values that need filling — all within a single low-cost call. Ideal for offline analytical pipelines processing up to 200 rows of transit data without needing live external data, predictions, or professional assessments.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, region, date) on any row causes validation error
- Invalid date format (not YYYY-MM-DD) triggers schema rejection
- base_index value pointing to a row index that doesn't exist in the submitted array
- All values for the chosen field are null, making mean/median fill undefined
- Payment of 0.01 USDC not completed — endpoint returns 402
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string | |
| base_index | integer |
Tags
x402
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