# Time Series Completeness — Grouped Numeric Summary + Trailing Mean Series

> Time Series Completeness — Grouped Numeric Summary + Trailing Mean Series 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).

Analyzes time series completeness data (observed vs expected points) by computing grouped numeric summaries and trailing mean series across up to 200 rows, producing two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-090?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-grouped-numeric-summary-trailing-mean-series-fd4c23ca
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_uyo31ySMjj5-qQbqqdskS

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-grouped-numeric-summary-trailing-mean-series-fd4c23ca -d '<json body>'
```

Example prompt: Can you run a grouped numeric summary and trailing mean analysis on my time series completeness data — I have observed and expected point counts for groups 'sensor-a' and 'sensor-b' across daily dates from 2026-10-01 to 2026-10-07, and I want the trailing mean computed with a window of 3?

## When to prefer this

Choose this endpoint when you need both grouped descriptive statistics and a rolling mean series for time series completeness data in a single low-cost call. It is purpose-built for observed vs expected point count analysis across named groups and dates, making it ideal for data quality monitoring workflows. Prefer it over general analytics tools when you want two complementary reports (summary + trend) delivered together for up to 200 rows at minimal cost.

## Known failure modes

- Fewer than 1 row or more than 200 rows submitted — request rejected
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) on any row
- Date strings not matching YYYY-MM-DD format — validation error
- Window parameter less than 2 or greater than 200 — rejected
- Null values in numeric fields may affect trailing mean computation
- Payment of 0.01 USDC not included or rejected — 402 response

## How this service works

Time series completeness — Grouped numeric summary + Trailing mean series: Grouped numeric summary + Trailing mean series 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

Two independent analytical reports: (1) a grouped numeric summary aggregating observed_points and expected_points statistics by dataset_group, and (2) a trailing mean series for the selected field computed with the specified rolling window — both derived entirely from the supplied rows, with no external data lookups.

## 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-grouped-numeric-summary-trailing-mean-series-fd4c23ca/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)