# Time Series Completeness — Exact Row Deduplication + Keyed Dataset Comparison

> Time Series Completeness — Exact Row Deduplication + Keyed Dataset Comparison 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).

Performs exact row deduplication and keyed dataset comparison on two sets of time series completeness records (observed_points vs expected_points), returning two independent analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-053?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-keyed-dataset-c28d2512
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_d7eh8j_8OLezvhGUpThmR

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-keyed-dataset-c28d2512 -d '<json body>'
```

Example prompt: Can you deduplicate these two sets of time series completeness records and compare them side by side — I have two datasets each with up to 50 rows of date, dataset_group, observed_points, and expected_points, and I need both a duplicate-row report and a keyed comparison of differences between the two?

## When to prefer this

Choose this endpoint when you need deterministic, purely local deduplication and cross-dataset comparison on time series completeness records (observed vs expected data points) with up to 200 rows, and you want two independent reports in a single $0.01 call — without requiring live data lookup, ML prediction, or external enrichment.

## Known failure modes

- Exceeding 200 rows per dataset triggers a validation error
- Missing required fields (row_id, date, dataset_group, observed_points, expected_points) causes rejection
- Invalid date format (non YYYY-MM-DD) fails schema validation
- Empty rows array (minItems:1 not met) returns an error
- Numeric values outside allowed range (-1e12 to 1e12) are rejected

## How this service works

Time series completeness — Exact row deduplication + Keyed dataset comparison: Exact row deduplication + Keyed dataset comparison 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) an exact row deduplication report identifying duplicate records within the supplied dataset(s), and (2) a keyed dataset comparison report highlighting rows that differ between the two supplied datasets based on observed_points and expected_points values — all computed locally without any external lookups or predictions.

## 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}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "expected_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "observed_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "expected_points": 1,
     "observed_points": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "expected_points": 2,
     "observed_points": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "expected_points": 3,
     "observed_points": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "expected_points": 4,
     "observed_points": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "other": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "observed_points",
     "expected_points"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "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
     }
    },
    "additiona
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-exact-row-deduplication-keyed-dataset-c28d2512/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)