# Time Series Completeness — Numeric Distribution & Row Ordering Analysis

> Time Series Completeness — Numeric Distribution & Row Ordering Analysis 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 records (observed vs expected data points) by generating both a numeric distribution report and a numeric row ordering report for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-073?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-numeric-distribution-row-ordering-analysis-bc72a4c3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_pGd-auIRAKKyjL-89ssbH

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-numeric-distribution-row-ordering-analysis-bc72a4c3 -d '<json body>'
```

Example prompt: I have 4 rows of time series completeness data — for group-a on 2026-10-01 I observed 10 out of 1 expected points, on 2026-10-03 I observed 15 out of 3 expected; for group-b on 2026-10-02 I observed 20 out of 2 expected, on 2026-10-04 I observed 30 out of 4 expected — can you run both the numeric distribution report and row ordering analysis on the observed_points field?

## When to prefer this

Choose this endpoint when you need both a distribution summary and a row-level ordering of numeric completeness metrics (observed vs expected points) for a time series dataset in a single $0.01 call. It is ideal for data quality audits, pipeline monitoring, and coverage analysis where you already have the completeness records in hand and need fast, local statistical reports without any external data fetching or prediction.

## Known failure modes

- Fewer than 1 row or more than 200 rows submitted — validation error
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) on any row — schema error
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Field value out of allowed numeric range (±1,000,000,000,000) — constraint error
- Invalid field enum value (not 'observed_points' or 'expected_points') — enum validation error
- Payment not included or insufficient — x402 payment required error

## How this service works

Time series completeness — Numeric distribution + Numeric row ordering: Numeric distribution + Numeric row ordering 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 for the supplied time series completeness rows: (1) a numeric distribution report summarizing statistical spread (e.g. min, max, mean, percentiles, histogram buckets) of the selected field (observed_points or expected_points), and (2) a numeric row ordering report that ranks rows by the selected field value. Both reports are computed locally from the supplied data with no external 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-numeric-distribution-row-ordering-analysis-bc72a4c3/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)