# Null Coverage Analytics — Daily Sum Series + Two-Measure Correlation

> Null Coverage Analytics — Daily Sum Series + 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 2026-10-14).

Computes a daily sum time series and a two-measure correlation report for user-supplied null coverage data (missing_values, total_values) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-141?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/null-coverage-analytics-daily-sum-series-two-measure-correlation-c45bea80
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_5jj0IpXM7c1Fz28kj6i5a

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-daily-sum-series-two-measure-correlation-c45bea80 -d '<json body>'
```

Example prompt: Can you run a daily sum series and two-measure correlation on these null coverage records — I have up to 50 rows each with a date, dataset_group, missing_values, and total_values — and focus the analysis on the missing_values field?

## When to prefer this

Choose this endpoint when you have pre-collected null coverage records (missing_values and total_values) organized by date and dataset group, and need both a daily aggregated time series and a statistical correlation between the two measures in a single low-cost call. Ideal for data quality audits, pipeline health checks, or completeness monitoring workflows where you already hold the raw records and need offline analytical summaries without any live data lookup or external enrichment.

## Known failure modes

- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — rejected, exceeds maximum
- Missing required fields (row_id, date, dataset_group) — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Null or out-of-range numeric values for missing_values or total_values — may produce incomplete correlation
- Insufficient date variance for meaningful time series — degenerate output possible

## How this service works

Null coverage — Daily sum series + Two-measure correlation: Daily sum series + 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 analytical reports computed locally from the supplied rows: (1) a daily sum series aggregating the selected field (missing_values or total_values) by date, and (2) a two-measure correlation report between missing_values and total_values across all supplied records. No external data is fetched; all computation is performed on the submitted rows (up to 200).

## 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-daily-sum-series-two-measure-correlation-c45bea80/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)