# Transport Ridership — Category Frequencies + Adjacent Row Changes

> Transport Ridership — Category Frequencies + Adjacent Row Changes 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).

Analyzes transport ridership data (passenger_count or service_count) by computing category frequencies and adjacent row changes for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-05-104?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transport-ridership-category-frequencies-adjacent-row-changes-49a2fdc7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_bi_G57vI1M-qOuTY-SA7y

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability transport-ridership-category-frequencies-adjacent-row-changes-49a2fdc7 -d '<json body>'
```

Example prompt: Can you run a category frequency and adjacent row change analysis on my transport ridership data? I have 10 rows with region, date, passenger_count, and service_count fields — analyze passenger_count please.

## When to prefer this

Choose this endpoint when you need two quick offline statistical reports — category frequency distributions and sequential row deltas — on transport ridership data with up to 200 rows. It is ideal when you already have the data locally and want lightweight batch analytics without any external API calls, predictions, or enrichment. Prefer it over general analytics platforms when cost predictability ($0.01 flat for both reports) and simplicity matter.

## Known failure modes

- Exceeds 200-row limit — request rejected, must split into smaller batches
- Missing required fields (row_id, region, date, passenger_count, service_count) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema validation failure
- Field selector not one of allowed enum values (passenger_count, service_count) — rejected
- Numeric values outside allowed range (-1e12 to 1e12) — schema error
- Payment not attached or insufficient USDC — x402 payment required response

## How this service works

Transport ridership — Category frequencies + Adjacent row changes: Category frequencies + Adjacent row changes 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 independent analytical reports: (1) category frequencies showing how often each region (or other categorical field) appears across the supplied rows, and (2) adjacent row changes showing the delta in the chosen numeric field (passenger_count or service_count) between each consecutive row — all computed locally with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "region",
     "date",
     "passenger_count",
     "service_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "region": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "service_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "passenger_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "region": "group-a",
     "row_id": "row-1",
     "service_count": 1,
     "passenger_count": 10
    },
    {
     "date": "2026-10-02",
     "region": "group-b",
     "row_id": "row-2",
     "service_count": 2,
     "passenger_count": 20
    },
    {
     "date": "2026-10-03",
     "region": "group-a",
     "row_id": "row-3",
     "service_count": 3,
     "passenger_count": 15
    },
    {
     "date": "2026-10-04",
     "region": "group-b",
     "row_id": "row-4",
     "service_count": 4,
     "passenger_count": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "passenger_count",
    "service_count"
   ],
   "type": "string",
   "default": "passenger_count"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transport-ridership-category-frequencies-adjacent-row-changes-49a2fdc7/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)