# Road Segment Observations — String Normalisation + Trailing Mean Series

> Road Segment Observations — String Normalisation + Trailing Mean Series 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).

Applies string normalisation and computes a trailing mean series on supplied road segment observation records (length_m, travel_seconds), returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-15-028?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/road-segment-observations-string-normalisation-trailing-mean-series-03ad0410
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_weA5zIWiC7-02Bv82Y2mG

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 road-segment-observations-string-normalisation-trailing-mean-series-03ad0410 -d '<json body>'
```

Example prompt: I have a list of road segment observations with length_m and travel_seconds across several station groups — can you normalise the station group strings and compute a trailing mean over a window of 3 for the travel_seconds field? Here are my rows: [{"row_id":"r1","station_group":"Group A","date":"2024-03-01","length_m":500,"travel_seconds":45},{"row_id":"r2","station_group":"group-a","date":"2024-03-02","length_m":500,"travel_seconds":50},{"row_id":"r3","station_group":"Group B","date":"2024-03-03","length_m":800,"travel_seconds":60}].

## When to prefer this

Choose this endpoint when you have up to 200 road segment observation records and need both string normalisation of categorical string fields and a trailing (rolling) mean series on a numeric measurement in a single call. It is cost-effective at $0.01 USDC for both reports simultaneously and operates entirely on supplied data with no external dependencies, making it suitable for offline analytics pipelines, data preparation workflows, or pre-ingestion quality checks on road monitoring datasets.

## Known failure modes

- Fewer than 1 row supplied — validation error
- More than 200 rows supplied — rejected with row limit error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Window size larger than number of rows — may produce sparse or empty trailing mean results
- Null numeric values in the target field — may reduce trailing mean coverage
- Invalid field enum value (not 'length_m' or 'travel_seconds') — schema rejection

## How this service works

Road segment observations — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied road segment observations records (length_m, travel_seconds). 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 string normalisation report on the station_group field across all supplied rows, and (2) a trailing mean series computed over the specified numeric field (length_m or travel_seconds) using the given window size. Results are derived purely from the supplied data with no external lookups or predictions.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/road-segment-observations-string-normalisation-trailing-mean-series-03ad0410/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)