# Tourism Observations — String Normalisation + Two-Measure Correlation

> Tourism Observations — String Normalisation + 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 2026-10-29).

Normalises region/date strings and computes Pearson correlation between visitor_count and overnight_stays across up to 200 tourism observation rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-14-033?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-29
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/tourism-observations-string-normalisation-two-measure-correlation-7375f878
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_AJNaDth3uRwC1Uc-DQ8fF

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 tourism-observations-string-normalisation-two-measure-correlation-7375f878 -d '<json body>'
```

Example prompt: I have 4 tourism observation rows — row-1 through row-4 for regions group-a and group-b, dated 2026-10-01 to 2026-10-04, with visitor counts of 10, 20, 15, 30 and overnight stays of 1, 2, 3, 4 — can you normalise the region and date strings and compute the correlation between visitor count and overnight stays across those rows?

## When to prefer this

Choose this endpoint when you have tourism observation data with string fields (region names, dates) that need normalisation AND you want a correlation analysis between visitor_count and overnight_stays in a single paid call. It is especially useful when you need both a data-quality string report and a statistical relationship report simultaneously for up to 200 rows, without involving any external data sources or predictions.

## Known failure modes

- Submission of more than 200 rows returns a validation error
- Missing required fields (row_id, region, date, visitor_count, overnight_stays) causes row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern are flagged or rejected
- All-null values for visitor_count or overnight_stays may cause correlation computation to fail
- Payment of less than 0.01 USDC results in a 402 Payment Required response

## How this service works

Tourism observations — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied tourism observations records (visitor_count, overnight_stays). 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) a string normalisation report covering the region and date fields across all submitted rows, and (2) a two-measure correlation report quantifying the statistical relationship (e.g. Pearson correlation) between visitor_count and overnight_stays across the dataset. No external lookups or predictions are made; all computation is local.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "region",
     "date",
     "visitor_count",
     "overnight_stays"
    ],
    "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
     },
     "visitor_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "overnight_stays": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "region": "group-a",
     "row_id": "row-1",
     "visitor_count": 10,
     "overnight_stays": 1
    },
    {
     "date": "2026-10-02",
     "region": "group-b",
     "row_id": "row-2",
     "visitor_count": 20,
     "overnight_stays": 2
    },
    {
     "date": "2026-10-03",
     "region": "group-a",
     "row_id": "row-3",
     "visitor_count": 15,
     "overnight_stays": 3
    },
    {
     "date": "2026-10-04",
     "region": "group-b",
     "row_id": "row-4",
     "visitor_count": 30,
     "overnight_stays": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/tourism-observations-string-normalisation-two-measure-correlation-7375f878/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)