# Time Series Completeness — Daily Sum + Secondary-Measure Weighted Mean

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

Computes daily sum and secondary-measure weighted mean analytics for time series completeness records (observed vs expected data points) across up to 200 rows in two independent reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-142?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-secondary-measure-weighted-mean-b0209447
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_BunNrXN9XA8q6gs7MySxw

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-secondary-measure-weighted-mean-b0209447 -d '<json body>'
```

Example prompt: I have up to 200 rows of daily time series completeness records with observed_points and expected_points for two dataset groups — can you compute the daily sum series and the secondary-measure weighted mean for me, using observed_points as the primary field?

## When to prefer this

Choose this endpoint when you need two complementary completeness analytics — a daily sum series and a weighted mean — computed together in a single cost-efficient call ($0.01 USDC for both reports). Ideal for data pipeline monitoring, sensor coverage audits, or any scenario where you track observed vs expected data point counts over time across multiple groups. Prefer this over single-report endpoints when you need both aggregation types simultaneously.

## Known failure modes

- Fewer than 1 or more than 200 rows submitted — request rejected
- Missing required fields (row_id, date, observed_points, expected_points) on any row — validation error
- Date strings not matching YYYY-MM-DD pattern — schema validation failure
- Null values in both observed_points and expected_points making weighted mean undefined
- Invalid field enum value (must be 'observed_points' or 'expected_points')

## How this service works

Time series completeness — Daily sum series + Secondary-measure weighted mean: Daily sum series + 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: (1) a daily sum series aggregating the selected measure (observed_points or expected_points) across all rows by date, and (2) a secondary-measure weighted mean that weights the primary field values by the companion measure — all computed locally with no external lookups. Up to 200 input rows supported per call.

## 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-secondary-measure-weighted-mean-b0209447/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)