# Sampling Observations Base-100 Series and IQR Outlier Flags

> Sampling Observations Base-100 Series and IQR Outlier Flags 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).

Computes a base-100 indexed time series and IQR-based outlier flags for up to 200 rows of supplied sampling observation data (sample_value, sample_weight).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-164?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/sampling-observations-base-100-series-and-iqr-outlier-flags-8d9f3bd7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Xoc8XbrmGcr_-MbDqy4Ab

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 sampling-observations-base-100-series-and-iqr-outlier-flags-8d9f3bd7 -d '<json body>'
```

Example prompt: Can you run a base-100 index and IQR outlier detection on my sample_value field for these 4 rows — row-1 on 2026-10-01 with value 10 and weight 1 (group-a), row-2 on 2026-10-02 with value 20 and weight 2 (group-b), row-3 on 2026-10-03 with value 15 and weight 3 (group-a), row-4 on 2026-10-04 with value 30 and weight 4 (group-b) — using row index 0 as the base?

## When to prefer this

Choose this endpoint when you have raw sampling observation data (with values and weights) and need both a base-100 normalized trend series and IQR-based statistical outlier flags in a single call, without any need for external data enrichment or prediction. Ideal for up to 200 rows of panel or time-series data where you want purely local, deterministic analytical output at minimal cost ($0.01 USDC for both reports).

## Known failure modes

- Fewer than 1 or more than 200 rows submitted — request rejected
- row_id or dataset_group exceeds 80 character maxLength — validation error
- date field does not match YYYY-MM-DD pattern — validation error
- base_index out of range 0–199 or exceeds row count — computation error
- sample_value or sample_weight outside ±1,000,000,000,000 bounds — validation error
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) on any row — error

## How this service works

Sampling observations — Base-100 series + IQR outlier flags: Base-100 series + IQR outlier flags for supplied sampling observations records (sample_value, sample_weight). 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 submitted rows: (1) a base-100 indexed series showing each row's value relative to the chosen baseline row, and (2) IQR outlier flags identifying which rows fall outside the interquartile range. 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",
     "sample_value",
     "sample_weight"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "sample_value": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "sample_weight": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "sample_value": 10,
     "dataset_group": "group-a",
     "sample_weight": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "sample_value": 20,
     "dataset_group": "group-b",
     "sample_weight": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "sample_value": 15,
     "dataset_group": "group-a",
     "sample_weight": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "sample_value": 30,
     "dataset_group": "group-b",
     "sample_weight": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "sample_value",
    "sample_weight"
   ],
   "type": "string",
   "default": "sample_value"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sampling-observations-base-100-series-and-iqr-outlier-flags-8d9f3bd7/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)