# Time Series Completeness — Exact Row Deduplication + Grouped Numeric Summary

> Time Series Completeness — Exact Row Deduplication + Grouped Numeric Summary 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).

Deduplicates exact rows and produces grouped numeric summary statistics for time series completeness records (observed_points, expected_points) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-040?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-exact-row-deduplication-grouped-numeric-e9c81b14
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_PQC7m2t7KAJU8Fp_3bpwl

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-exact-row-deduplication-grouped-numeric-e9c81b14 -d '<json body>'
```

Example prompt: I have up to 200 rows of time series completeness records with observed_points and expected_points per date and dataset_group — can you deduplicate exact duplicate rows and give me a grouped numeric summary of the observed_points field across all groups?

## When to prefer this

Choose this endpoint when you need both exact duplicate row removal and grouped numeric summaries for time series completeness data in a single call at minimal cost ($0.01 USDC for both reports). It is ideal for data quality pipelines that track observed vs expected data point counts across groups and dates, and need lightweight local analytics without any external lookups or predictions.

## Known failure modes

- Exceeding 200 rows results in rejection or truncation
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) causes validation errors
- Invalid date format (non-YYYY-MM-DD) triggers schema validation failure
- Numeric values outside the allowed range (-1e12 to 1e12) are rejected
- Submitting fewer than 1 row causes a minItems validation error

## How this service works

Time series completeness — Exact row deduplication + Grouped numeric summary: Exact row deduplication + Grouped numeric summary 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: (1) an exact row deduplication report identifying and removing duplicate entries from the submitted rows, and (2) a grouped numeric summary of the chosen field (observed_points or expected_points) aggregated by dataset_group, including descriptive statistics such as counts, totals, and averages per group.

## 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-exact-row-deduplication-grouped-numeric-e9c81b14/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)