# Simulation Caches IQR Outlier Flags + Explicit Missing-Value Fill

> Simulation Caches IQR Outlier Flags + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).

Runs two local analytical reports on simulation cache records: IQR-based outlier detection and explicit missing-value imputation for cache_gb and simulation_seconds fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-08-180?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/simulation-caches-iqr-outlier-flags-explicit-missing-value-fill-996d0403
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_SSQQD73JzKTq9rIuzuHy5

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 simulation-caches-iqr-outlier-flags-explicit-missing-value-fill-996d0403 -d '<json body>'
```

Example prompt: I have up to 200 rows of simulation cache records with cache_gb and simulation_seconds — can you flag any IQR outliers in cache_gb and fill any missing values using median imputation?

## When to prefer this

Use this endpoint when you have up to 200 rows of simulation cache records and need both IQR outlier detection and missing-value imputation in a single low-cost call ($0.01 USDC). Ideal for lightweight, offline data quality checks on simulation cache metrics (cache_gb, simulation_seconds) without requiring an external data science environment or live prediction service.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, date, cache_gb, simulation_seconds, asset_group) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Unsupported method enum value returns validation error
- All values present with no nulls results in empty missing-value fill report
- All values within IQR results in no outlier flags

## How this service works

Simulation caches — IQR outlier flags + Explicit missing-value fill: IQR outlier flags + Explicit missing-value fill for supplied simulation caches records (cache_gb, simulation_seconds). 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 per call: (1) IQR-based outlier flags indicating which rows fall outside the interquartile range for the specified field, and (2) a missing-value fill report showing which null values were imputed and what values were substituted (zero, mean, or median). Results cover up to 200 input rows and are computed locally without any external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "asset_group",
     "date",
     "cache_gb",
     "simulation_seconds"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "cache_gb": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "asset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "simulation_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "cache_gb": 10,
     "asset_group": "group-a",
     "simulation_seconds": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "cache_gb": 20,
     "asset_group": "group-b",
     "simulation_seconds": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "cache_gb": 15,
     "asset_group": "group-a",
     "simulation_seconds": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "cache_gb": 30,
     "asset_group": "group-b",
     "simulation_seconds": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "cache_gb",
    "simulation_seconds"
   ],
   "type": "string",
   "default": "cache_gb"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/simulation-caches-iqr-outlier-flags-explicit-missing-value-fill-996d0403/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)