# Sampling Observations Analytics: Record Quality Audit + String Normalisation + Equal-Width Histogram

> Sampling Observations Analytics: Record Quality Audit + 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 2026-10-15).

Runs three bundled local analytical reports — record quality audit, string normalisation, and equal-width histogram — on up to 200 sampling observation rows (sample_value, sample_weight).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-202?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/sampling-observations-analytics-record-quality-audit-string-c68d8779
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Yho_eoGoPcwNDnLgF0AqH

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 sampling-observations-analytics-record-quality-audit-string-c68d8779 -d '<json body>'
```

Example prompt: Can you run a full quality audit, string normalisation, and a 10-bin equal-width histogram on my sampling observations dataset — I have 50 rows with sample_value and sample_weight fields, grouped by dataset_group, and I want the histogram on sample_value?

## When to prefer this

Choose this endpoint when you need three bundled analytical reports (quality audit, string normalisation, histogram) on sampling observation data in a single cheap call ($0.01 USDC). It is ideal for data pipeline pre-checks, exploratory profiling of weighted sample datasets, or validating batches of up to 200 rows before downstream modelling. Prefer it over separate tools when you want all three reports in one round-trip with no external data dependencies.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Invalid date format (not YYYY-MM-DD) causes row rejection
- bins value outside 1–30 range triggers a schema validation failure
- Numeric values outside ±1,000,000,000,000 are rejected
- Missing required fields (row_id, date, sample_value, sample_weight, dataset_group) cause row-level errors
- Payment failure (insufficient USDC) blocks the request

## How this service works

Sampling observations — Record quality audit + String normalisation + Equal-width histogram: Record quality audit + String normalisation + Equal-width histogram for supplied sampling observations records (sample_value, sample_weight). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Three independent analytical reports: (1) a record quality audit flagging missing, invalid, or out-of-range values across all rows; (2) a string normalisation report detailing transformations applied to text fields like dataset_group and date; and (3) an equal-width histogram report over the chosen numeric field (sample_value or sample_weight) divided into the requested number of bins — all computed locally without any external data lookup.

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sampling-observations-analytics-record-quality-audit-string-c68d8779/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)