# Label Review Analytics: Category Frequencies & Numeric Row Ordering

> Label Review Analytics: Category Frequencies & Numeric Row Ordering 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 category frequency distributions and numeric row ordering for up to 200 label review records, returning two independent analytical reports in a single call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-100?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/label-review-analytics-category-frequencies-numeric-row-ordering-1def0e42
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VEAtqF4X5ItPeFCL8uZC6

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 label-review-analytics-category-frequencies-numeric-row-ordering-1def0e42 -d '<json body>'
```

Example prompt: I have 150 label review records with dataset groups, dates, reviewed_records, and changed_labels — can you give me a category frequency breakdown by dataset_group and also rank the rows numerically by reviewed_records?

## When to prefer this

Choose this endpoint when you need both a categorical frequency breakdown and a numeric row ranking for label review data in a single low-cost call. Ideal for ML data labeling pipelines that need quick QA reports on review batches up to 200 rows without requiring any external data sources, predictions, or live lookups. Prefer this over general analytics tools when working specifically with label review records structured around dataset_group, reviewed_records, and changed_labels fields.

## Known failure modes

- Submitting more than 200 rows returns an error — batch must be split
- Missing required fields (row_id, dataset_group, date, reviewed_records, changed_labels) on any row causes validation failure
- Invalid date format (not YYYY-MM-DD) triggers pattern validation error
- Numeric fields outside the allowed range (±1,000,000,000,000) are rejected
- Empty rows array is not accepted — at least 1 row required
- Invalid field enum value (not 'reviewed_records' or 'changed_labels') causes error

## How this service works

Label review — Category frequencies + Numeric row ordering: Category frequencies + Numeric row ordering for supplied label review records (reviewed_records, changed_labels). 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

Two independent analytical reports: (1) a category frequency table showing how often each dataset_group value appears across the supplied rows, and (2) a numeric row ordering of all submitted records ranked by the chosen field (reviewed_records or changed_labels). Both reports are computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/label-review-analytics-category-frequencies-numeric-row-ordering-1def0e42/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)