# Time Series Completeness: Two-Measure Correlation + Secondary Weighted Mean

> Time Series Completeness: Two-Measure Correlation + Secondary Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).

Computes two-measure correlation and secondary-measure weighted mean analytics for time series completeness records (observed vs expected data points), processing up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-181?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/time-series-completeness-two-measure-correlation-secondary-weighted-b5cd4834
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ZJYhNR-YbKnsdPgbT7hoe

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 time-series-completeness-two-measure-correlation-secondary-weighted-b5cd4834 -d '<json body>'
```

Example prompt: I have up to 50 rows of daily time series completeness records with observed_points and expected_points per dataset group — can you run the two-measure correlation plus secondary weighted mean reports on them?

## When to prefer this

Choose this endpoint when you need offline statistical computation of correlation and weighted mean for time series completeness data (observed vs expected point counts) without requiring any external lookups or predictions. Ideal for data quality pipelines, monitoring dashboards, or reporting workflows that need two bundled analytical outputs in a single low-cost call for up to 200 rows.

## Known failure modes

- More than 200 rows submitted — request rejected at input validation
- Missing required fields (row_id, date, observed_points, expected_points) — validation error
- Date field not in YYYY-MM-DD format — pattern validation failure
- Null values in numeric fields may affect correlation computation
- Invalid field enum value (not observed_points or expected_points) — rejected
- Payment not included or insufficient USDC — x402 payment required error

## How this service works

Time series completeness — Two-measure correlation + Secondary-measure weighted mean: Two-measure correlation + Secondary-measure weighted mean for supplied time series completeness records (observed_points, expected_points). 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 for the submitted time series completeness data: (1) a two-measure correlation report showing the statistical relationship between observed_points and expected_points across rows, and (2) a secondary-measure weighted mean report for the selected field (observed_points or expected_points). Both reports use local analytical engines with no external data lookup.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "observed_points",
     "expected_points"
    ],
    "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_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "observed_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "expected_points": 1,
     "observed_points": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "expected_points": 2,
     "observed_points": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "expected_points": 3,
     "observed_points": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "expected_points": 4,
     "observed_points": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "observed_points",
    "expected_points"
   ],
   "type": "string",
   "default": "observed_points"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-two-measure-correlation-secondary-weighted-b5cd4834/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)