# Schema Conformity IQR Outlier Flags + Missing-Value Fill

> Schema Conformity IQR Outlier Flags + 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 2026-10-14).

Detects IQR-based outliers and fills explicit missing values in schema conformity records (valid_records, checked_records) for up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-180?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-iqr-outlier-flags-missing-value-fill-82abf48a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_KhHEqgZjwjnBRmQKCVjTU

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 schema-conformity-iqr-outlier-flags-missing-value-fill-82abf48a -d '<json body>'
```

Example prompt: I have a schema conformity dataset with up to 50 rows, each with a date, dataset_group, valid_records, and checked_records — can you flag IQR outliers and fill any missing values in the valid_records column using median imputation?

## When to prefer this

Choose this endpoint when you need both IQR-based outlier flagging and missing-value imputation on schema conformity metrics (valid_records, checked_records) in a single call for up to 200 rows. It is ideal for lightweight, offline data quality checks where no external data sources, live predictions, or professional assessments are required. Prefer this over general-purpose analytics when the input schema exactly matches the conformity record structure and you want both reports for a flat $0.01 USDC fee.

## Known failure modes

- Fewer than 1 row provided — minItems validation error
- More than 200 rows submitted — maxItems limit exceeded
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Field value not in enum ['valid_records','checked_records'] — enum validation error
- Method value not in enum ['zero','mean','median'] — enum validation error
- All values in selected field are null — IQR computation may be undefined
- Numeric values outside ±1,000,000,000,000 range — schema rejection

## How this service works

Schema conformity — IQR outlier flags + Explicit missing-value fill: IQR outlier flags + Explicit missing-value fill for supplied schema conformity records (valid_records, checked_records). 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 analytical reports: (1) IQR outlier flags per row for the selected field, indicating which rows fall outside the interquartile range; (2) a missing-value fill report showing imputed values for null entries using the chosen method (zero, mean, or median). Results are computed locally with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "valid_records",
     "checked_records"
    ],
    "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
     },
     "valid_records": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "checked_records": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "valid_records": 10,
     "checked_records": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "valid_records": 20,
     "checked_records": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "valid_records": 15,
     "checked_records": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "valid_records": 30,
     "checked_records": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "valid_records",
    "checked_records"
   ],
   "type": "string",
   "default": "valid_records"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-iqr-outlier-flags-missing-value-fill-82abf48a/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)