# Duplicate Observations IQR Outlier Flags and Missing Value Fill

> Duplicate Observations IQR Outlier Flags and 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 2026-10-20).

Analyzes up to 200 rows of duplicate-observation records to flag IQR-based outliers and fill missing values in duplicate_rows or total_rows fields, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-180?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/duplicate-observations-iqr-outlier-flags-and-missing-value-fill-a4e3afe5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_DTL9Q0VrIJlBuKp6Vcr_T

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 duplicate-observations-iqr-outlier-flags-and-missing-value-fill-a4e3afe5 -d '<json body>'
```

Example prompt: I have up to 200 rows of dataset duplication observations with fields like duplicate_rows and total_rows — can you run IQR outlier flagging and fill any missing duplicate_rows values using median imputation on this data?

## When to prefer this

Choose this endpoint when you need simultaneous IQR outlier detection and missing-value imputation on batch duplicate-observation records (up to 200 rows) in a single low-cost call. It is especially useful for data quality pipelines auditing dataset duplication metrics across groups and dates, where both anomaly flagging and null filling are needed together without external data access or live predictions.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) cause validation error
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- field or method enum values not matching allowed options return error
- Insufficient USDC balance or x402 payment failure blocks execution
- All values for selected field are null — imputation may be undefined or trivial

## How this service works

Duplicate observations — IQR outlier flags + Explicit missing-value fill: IQR outlier flags + Explicit missing-value fill for supplied duplicate observations records (duplicate_rows, total_rows). 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 analytical reports per call: (1) IQR-based outlier flags indicating which observations fall outside the interquartile range for the selected field, and (2) explicit missing-value fill results replacing nulls in that field using the chosen method (zero, mean, or median). Both reports are computed locally on 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",
     "duplicate_rows",
     "total_rows"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "total_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "duplicate_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "total_rows": 1,
     "dataset_group": "group-a",
     "duplicate_rows": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "total_rows": 2,
     "dataset_group": "group-b",
     "duplicate_rows": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "total_rows": 3,
     "dataset_group": "group-a",
     "duplicate_rows": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "total_rows": 4,
     "dataset_group": "group-b",
     "duplicate_rows": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "duplicate_rows",
    "total_rows"
   ],
   "type": "string",
   "default": "duplicate_rows"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/duplicate-observations-iqr-outlier-flags-and-missing-value-fill-a4e3afe5/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)