# Time Series Completeness — IQR Outlier Flags + Keyed Dataset Comparison

> Time Series Completeness — IQR Outlier Flags + 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 2026-10-15).

Analyzes time series completeness records (observed vs expected data points) using IQR-based outlier detection and keyed dataset comparison, producing two independent analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-179?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-iqr-outlier-flags-keyed-dataset-comparison-e7a2487d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_6VvwvLaHlV7pgtsGqTui6

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-iqr-outlier-flags-keyed-dataset-comparison-e7a2487d -d '<json body>'
```

Example prompt: Can you run IQR outlier detection and a keyed dataset comparison on my time series completeness data? I have two sets of up to 200 rows each with observed_points and expected_points per date and dataset_group — flag which rows are outliers and show me how the two datasets differ.

## When to prefer this

Choose this endpoint when you need both IQR-based outlier detection and a keyed dataset comparison in a single low-cost call ($0.01 USDC) on pre-collected time series completeness records. It is ideal for data quality pipelines that track observed vs expected data point counts per date and group. Prefer this over separate analysis tools when your dataset fits within 200 rows and you want two complementary views — statistical outlier flagging plus record-level cross-dataset diffing — without sending data to an external live system.

## Known failure modes

- Fewer than 1 row supplied — rejected by minItems constraint
- More than 200 rows supplied — rejected by maxItems constraint
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) on any row — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- row_id longer than 80 characters — rejected
- IQR computation may be unreliable with very few rows (e.g. fewer than 4–5 data points)
- Payment failure via x402 protocol — endpoint not invoked

## How this service works

Time series completeness — IQR outlier flags + Keyed dataset comparison: IQR outlier flags + 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 independent reports: (1) an IQR outlier detection report that flags rows where the selected field (observed_points or expected_points) falls outside the interquartile range boundaries, and (2) a keyed dataset comparison report that matches rows by row_id across the primary and secondary datasets and identifies differences. Both reports are computed locally from the supplied data with no external 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}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "expected_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "observed_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "expected_points": 1,
     "observed_points": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "expected_points": 2,
     "observed_points": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "expected_points": 3,
     "observed_points": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "expected_points": 4,
     "observed_points": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "observed_points",
    "expected_points"
   ],
   "type": "string",
   "default": "observed_points"
  },
  "other": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "observed_points",
     "expected_points"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "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-iqr-outlier-flags-keyed-dataset-comparison-e7a2487d/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
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