# Sampling Observations — Equal-Width Histogram + IQR Outlier Flags

> Sampling Observations — Equal-Width Histogram + 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 2026-10-15).

Computes an equal-width histogram and IQR-based outlier flags for up to 200 sampling observation records (sample_value or sample_weight).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-170?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/sampling-observations-equal-width-histogram-iqr-outlier-flags-df8d33df
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Px_tYb3rd6cPbNk9Cu0pt

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-equal-width-histogram-iqr-outlier-flags-df8d33df -d '<json body>'
```

Example prompt: Analyze the distribution of my sample_value field across these 12 sampling records — group them into 6 equal-width bins and flag any IQR outliers: [row-1, 2024-01-01, group-a, value=42, weight=1], [row-2, 2024-01-02, group-a, value=300, weight=2], etc.

## When to prefer this

Choose this endpoint when you have up to 200 tabular sampling observation records and need both a distributional summary (histogram) and anomaly identification (IQR outlier flags) in a single $0.01 call. It is ideal for lightweight, offline statistical QA of numeric measurement or weight data without needing an external data science platform. Prefer it over general analytics APIs when your data fits the specific sample_value/sample_weight schema and you want deterministic, reproducible results with no external data transmission beyond your supplied rows.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems limit
- Invalid date format (not YYYY-MM-DD) causes row validation failure
- sample_value or sample_weight outside ±1,000,000,000,000 range causes schema rejection
- bins parameter exceeds 30 or is less than 1 — validation error
- Missing required fields (row_id, date, dataset_group) causes row rejection
- All values are identical — histogram bins may be degenerate, IQR may be zero

## How this service works

Sampling observations — Equal-width histogram + IQR outlier flags: Equal-width histogram + 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: (1) an equal-width histogram partitioning the chosen field (sample_value or sample_weight) into the specified number of bins with counts per bin, and (2) IQR-based outlier flags identifying which rows contain values outside the interquartile fence. Both reports are computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sampling-observations-equal-width-histogram-iqr-outlier-flags-df8d33df/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)