# Time Series Completeness — Daily Sum + Two-Measure Correlation

> Time Series Completeness — Daily Sum + 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 2026-10-15).

Computes a daily sum series and a two-measure correlation report for time series completeness data (observed vs expected points) over up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-141?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/time-series-completeness-daily-sum-two-measure-correlation-75b61d81
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_b4hSqwr3bNcgl5dlgL6C9

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-daily-sum-two-measure-correlation-75b61d81 -d '<json body>'
```

Example prompt: I have 50 rows of daily completeness data with observed_points and expected_points per dataset group — can you run the daily sum series and two-measure correlation reports on it?

## When to prefer this

Choose this endpoint when you have raw daily time series completeness records (observed vs expected data points) and need both an aggregated daily sum trend and a linear correlation between the two measures in a single low-cost call. Ideal for data quality monitoring, pipeline auditing, and sensor coverage checks where you supply your own data and need fast, local statistical summaries without external enrichment or live data access.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, observed_points, expected_points) on any row causes validation error
- Malformed date format (not YYYY-MM-DD) triggers schema validation failure
- Null values in both numeric fields may reduce correlation validity
- Insufficient data variation may yield low-significance correlation results

## How this service works

Time series completeness — Daily sum series + Two-measure correlation: Daily sum series + Two-measure correlation 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 analytical reports computed from the supplied rows: (1) a daily sum series aggregating the selected field by date, and (2) a two-measure correlation between observed_points and expected_points. Both reports are computed locally with no external lookups or predictions, covering up to 200 input rows.

## 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-daily-sum-two-measure-correlation-75b61d81/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)