# Time Series Completeness — Date by Category Pivot + Keyed Dataset Comparison

> Time Series Completeness — Date by Category Pivot + 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 2026-10-19).

Analyzes time series completeness records by producing a date-by-category pivot table and a keyed dataset comparison report from supplied observed/expected data points.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-188?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/time-series-completeness-date-by-category-pivot-keyed-dataset-8eed3746
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_XSEOUyZ08lNxpTKWlCZVy

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-date-by-category-pivot-keyed-dataset-8eed3746 -d '<json body>'
```

Example prompt: Can you run a date-by-category pivot and a keyed dataset comparison on my time series completeness records? I have two datasets — the primary rows include dates like 2026-10-01 through 2026-10-04, groups 'group-a' and 'group-b', with observed_points and expected_points values, and a second dataset to compare against — use 'observed_points' as the field to analyze.

## When to prefer this

Choose this endpoint when you need to simultaneously produce a date-by-category pivot AND compare two versions or snapshots of a time series completeness dataset in a single paid call. It is ideal for data quality audits, ETL validation, and completeness monitoring where you have structured rows with observed vs. expected point counts grouped by category and date. Prefer this over single-report endpoints when you need both pivot and comparison analytics at once to minimize cost.

## Known failure modes

- Empty rows array — request rejected (minItems: 1)
- Rows exceed 200 — request rejected (maxItems: 200)
- Invalid date format (not YYYY-MM-DD) — validation error
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) — schema validation failure
- Invalid field enum value (not 'observed_points' or 'expected_points') — error
- Numeric values outside allowed range (±1,000,000,000,000) — validation error
- Payment failure — x402 payment not processed, request blocked

## How this service works

Time series completeness — Date by category pivot + Keyed dataset comparison: Date by category pivot + 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

Returns two analytical reports: (1) a date-by-category pivot table showing the selected field (observed_points or expected_points) broken down by date and dataset_group, and (2) a keyed dataset comparison between the primary rows and the secondary 'other' dataset, highlighting differences in completeness metrics. Up to 200 rows processed 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}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "expected_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "observed_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "expected_points": 1,
     "observed_points": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "expected_points": 2,
     "observed_points": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "expected_points": 3,
     "observed_points": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "expected_points": 4,
     "observed_points": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "observed_points",
    "expected_points"
   ],
   "type": "string",
   "default": "observed_points"
  },
  "other": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "observed_points",
     "expected_points"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "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":
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-date-by-category-pivot-keyed-dataset-8eed3746/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)