# Null Coverage Analytics: Category Frequencies + Two-Measure Correlation

> Null Coverage Analytics: Category Frequencies + Two-Measure Correlation 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).

Analyzes null/missing-value coverage records by computing category frequencies across dataset groups and Pearson correlation between missing_values and total_values, returning two independent analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-108?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-category-frequencies-two-measure-correlation-c542a95a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Hhbo0L4QOHjqiJKhyIigW

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-category-frequencies-two-measure-correlation-c542a95a -d '<json body>'
```

Example prompt: I have null coverage records for my pipeline runs — can you compute the category frequencies by dataset group and the correlation between missing_values and total_values for these rows: [{row_id: 'r1', dataset_group: 'sales', date: '2024-01-01', missing_values: 50, total_values: 500}, {row_id: 'r2', dataset_group: 'marketing', date: '2024-01-02', missing_values: 20, total_values: 300}]?

## When to prefer this

Choose this endpoint when you have tabular null-coverage or data-completeness records with a categorical grouping column and two numeric measures, and you need both a group frequency summary and a correlation statistic in a single low-cost call. It is ideal for data quality monitoring pipelines that track missing values across named dataset groups over time. Prefer it over generic statistics APIs when your data fits the specific schema (row_id, dataset_group, date, missing_values, total_values) and you want both reports bundled for $0.01.

## Known failure modes

- Fewer than 1 row submitted — fails minItems validation
- More than 200 rows submitted — fails maxItems validation
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) — validation error
- Date not matching YYYY-MM-DD format — pattern validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — validation error
- All missing_values or total_values are null — correlation computation may be undefined or return NaN

## How this service works

Null coverage — Category frequencies + Two-measure correlation: Category frequencies + Two-measure correlation 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 category frequency table showing how often each dataset_group value appears across the submitted rows, and (2) a two-measure correlation analysis between the missing_values and total_values numeric fields across all submitted records. Both reports are computed locally from 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",
     "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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/null-coverage-analytics-category-frequencies-two-measure-correlation-c542a95a/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)