# Data Freshness String Normalisation + Equal-Width Histogram

> Data Freshness String Normalisation + Equal-Width Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).

Computes string normalisation and an equal-width histogram for data freshness records (age_minutes or record_count) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-06-031?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-freshness-string-normalisation-equal-width-histogram-2f75b3bc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_fxYSuKP0UhxdhLMo7kw0d

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 data-freshness-string-normalisation-equal-width-histogram-2f75b3bc -d '<json body>'
```

Example prompt: Analyse my data freshness records and give me a string normalisation report plus an equal-width histogram with 10 bins on the age_minutes field — here are my rows: [{"row_id":"r1","dataset_group":"sales","date":"2024-06-01","age_minutes":5,"record_count":120},{"row_id":"r2","dataset_group":"marketing","date":"2024-06-02","age_minutes":45,"record_count":80}].

## When to prefer this

Choose this endpoint when you need lightweight, local statistical profiling of data freshness records without any external API calls or predictions. It is ideal for data quality pipelines that need both string normalisation and histogram binning in a single cheap call ($0.01 USDC) on batches up to 200 rows. Prefer it over general-purpose analytics services when you specifically want equal-width histogram bucketing of age_minutes or record_count alongside string normalisation in a single combined report.

## Known failure modes

- More than 200 rows supplied — request is rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- bins value outside 1–30 range — validation error
- Unknown field value (not age_minutes or record_count) — enum validation error
- All values for the selected field are null — histogram cannot be computed
- Malformed row object missing required fields — schema validation error

## How this service works

Data freshness — String normalisation + Equal-width histogram: String normalisation + Equal-width histogram for supplied data freshness records (age_minutes, record_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 data freshness rows: (1) a string normalisation summary covering the text fields, and (2) an equal-width histogram of the selected numeric field (age_minutes or record_count) partitioned into the requested number of bins, including bin edges and counts per bin. No external lookups or predictions are made.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "age_minutes",
     "record_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "age_minutes": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "record_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "age_minutes": 10,
     "record_count": 1,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "age_minutes": 20,
     "record_count": 2,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "age_minutes": 15,
     "record_count": 3,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "age_minutes": 30,
     "record_count": 4,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "age_minutes",
    "record_count"
   ],
   "type": "string",
   "default": "age_minutes"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-freshness-string-normalisation-equal-width-histogram-2f75b3bc/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)