# Feature Availability Analytics — Grouped Numeric Summary & Category Frequencies

> Feature Availability Analytics — Grouped Numeric Summary & Category Frequencies is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Computes a grouped numeric summary and category frequency distribution for feature availability data (populated_features and expected_features) across up to 200 rows, using local analytical engines.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-086?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/feature-availability-analytics-grouped-numeric-summary-category-1fae44dc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Iud25WJ_4Olrep706SCri

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 feature-availability-analytics-grouped-numeric-summary-category-1fae44dc -d '<json body>'
```

Example prompt: Analyze my feature availability data — I have 4 rows with dataset groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, with populated_features values of 10, 20, 15, 30 and expected_features of 1, 2, 3, 4. Give me a grouped numeric summary and category frequency breakdown for the populated_features field.

## When to prefer this

Choose this endpoint when you need quick grouped statistical summaries and category frequency counts for feature availability records without requiring live data lookups, external data enrichment, or predictions. It is ideal for data quality audits, ML pipeline monitoring, and dataset completeness reporting where you already have the raw records and just need structured aggregate analytics across up to 200 rows at very low cost ($0.01 USDC for both reports).

## Known failure modes

- Fewer than 1 row submitted — returns validation error
- More than 200 rows submitted — request rejected, exceeds maxItems limit
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Missing required fields (row_id, dataset_group, date, populated_features, expected_features) — rejected with missing field error
- field enum value not in ['populated_features','expected_features'] — invalid enum error
- Null values in numeric fields may affect summary statistics depending on implementation

## How this service works

Feature availability — Grouped numeric summary + Category frequencies: Grouped numeric summary + Category frequencies for supplied feature availability records (populated_features, expected_features). 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 grouped numeric summary (e.g. mean, min, max, count, std dev) of the selected numeric field (populated_features or expected_features) broken down by dataset_group, and (2) a category frequency table showing how often each dataset_group appears across the supplied rows. Both reports are computed locally from the submitted 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",
     "populated_features",
     "expected_features"
    ],
    "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
     },
     "expected_features": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "populated_features": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "expected_features": 1,
     "populated_features": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "expected_features": 2,
     "populated_features": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "expected_features": 3,
     "populated_features": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "expected_features": 4,
     "populated_features": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "populated_features",
    "expected_features"
   ],
   "type": "string",
   "default": "populated_features"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/feature-availability-analytics-grouped-numeric-summary-category-1fae44dc/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)