# Null Coverage Grouped Numeric Summary with IQR Outlier Flags

> Null Coverage Grouped Numeric Summary with IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).

Computes grouped numeric summary statistics and IQR-based outlier flags for null coverage data (missing_values, total_values) across up to 200 rows, producing 2 independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-094?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/null-coverage-grouped-numeric-summary-with-iqr-outlier-flags-d9cc6fc3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_eRP80lwb1vWcV11M2riAA

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 null-coverage-grouped-numeric-summary-with-iqr-outlier-flags-d9cc6fc3 -d '<json body>'
```

Example prompt: Can you run a grouped numeric summary and IQR outlier detection on my null coverage records? I have rows with missing_values and total_values fields for groups like 'group-a' and 'group-b' across dates in October 2026 — flag any outliers and summarize the missing_values field by group.

## When to prefer this

Choose this endpoint when you have pre-collected null coverage or data quality records (missing_values and total_values) that need grouped summary statistics and IQR-based outlier detection in a single call. It is ideal for offline or batch data quality analysis where you supply your own data rather than fetching live datasets. Prefer this over generic statistics endpoints when you specifically need group-aware summaries alongside outlier flagging for completeness metrics.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejected
- Empty rows array — no data to analyze
- Invalid field enum value (not 'missing_values' or 'total_values') — error response

## How this service works

Null coverage — Grouped numeric summary + IQR outlier flags: Grouped numeric summary + IQR outlier flags for supplied null coverage records (missing_values, total_values). 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 with statistics (mean, median, min, max, std dev, etc.) segmented by dataset_group for the selected field, and (2) IQR-based outlier flags identifying which rows fall beyond 1.5× the interquartile range. Covers up to 200 input rows with no external data lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/null-coverage-grouped-numeric-summary-with-iqr-outlier-flags-d9cc6fc3/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)