# Transport Ridership Trailing Mean Series + Two-Measure Correlation

> Transport Ridership Trailing Mean Series + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).

Computes a trailing moving average series and a two-measure correlation analysis on supplied transport ridership data (passenger_count and service_count) for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-05-150?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transport-ridership-trailing-mean-series-two-measure-correlation-a59ea791
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_NSkrBBccRAi_BBUSdHjhC

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-trailing-mean-series-two-measure-correlation-a59ea791 -d '<json body>'
```

Example prompt: I have 4 rows of transit ridership data — row-1 through row-4 across regions group-a and group-b, each with passenger_count and service_count values — can you compute a trailing mean series with a window of 3 on the passenger_count field and also run the two-measure correlation between passenger_count and service_count?

## When to prefer this

Choose this endpoint when you have raw transport ridership records with passenger_count and service_count fields and need both a rolling/trailing average trend series and a correlation analysis between the two measures in a single call. It is purpose-built for transit analytics on supplied data up to 200 rows and avoids needing two separate calls. Prefer alternatives if you need histogram bucketing, outlier detection, or daily sum aggregations instead.

## Known failure modes

- Fewer than 1 row submitted — minimum items validation failure
- window size exceeds number of rows — insufficient data for trailing mean
- invalid date format (not YYYY-MM-DD) — pattern validation error
- row_id missing or empty — required field violation
- numeric values outside allowed range (±1,000,000,000,000) — schema rejection
- more than 200 rows submitted — maxItems exceeded

## How this service works

Transport ridership — Trailing mean series + Two-measure correlation: Trailing mean series + Two-measure correlation 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: (1) a trailing mean time series computed over the specified window for the chosen field (passenger_count or service_count), and (2) a Pearson or similar correlation coefficient between passenger_count and service_count across the supplied rows. Results are derived entirely from the submitted data 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transport-ridership-trailing-mean-series-two-measure-correlation-a59ea791/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)