# Null Coverage Analytics — Grouped Numeric Summary & Date-by-Category Pivot

> Null Coverage Analytics — Grouped Numeric Summary & Date-by-Category Pivot 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).

Generates two local analytical reports (grouped numeric summary and date-by-category pivot) for null/missing-value coverage data supplied by the caller.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-097?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-analytics-grouped-numeric-summary-date-by-category-pivot-eba2b31b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_KvctnEy9vnijd7UAUK_SF

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-analytics-grouped-numeric-summary-date-by-category-pivot-eba2b31b -d '<json body>'
```

Example prompt: Analyze my null coverage data — I have up to 200 rows each with a row_id, dataset_group, date, missing_values, and total_values — and give me both a grouped numeric summary and a date-by-category pivot for the missing_values field.

## When to prefer this

Choose this endpoint when you have pre-collected null coverage records (with missing_values and total_values per row) and need two analytical views — a grouped numeric summary and a date-by-category pivot — computed entirely from your supplied data without any live lookups or external data enrichment. Ideal for data quality audits, ETL pipeline monitoring, and completeness reporting where the data is already on hand and you need structured analytical output at very low cost ($0.01 USDC for both reports).

## Known failure modes

- Missing required row fields (row_id, dataset_group, date, missing_values, total_values) causes validation error
- More than 200 rows submitted exceeds the row limit and will be rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Selecting a field value outside the enum [missing_values, total_values] returns an error
- Submitting an empty rows array (minItems:1 violated) causes rejection
- Null values for numeric fields may affect aggregation results if not handled by caller

## How this service works

Null coverage — Grouped numeric summary + Date by category pivot: Grouped numeric summary + Date by category pivot 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 reports: (1) a grouped numeric summary of the selected field (missing_values or total_values) broken down by dataset_group, and (2) a pivot table of that field by date and category — both computed locally from the supplied rows, with no external lookups or predictions.

## 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-analytics-grouped-numeric-summary-date-by-category-pivot-eba2b31b/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)