# Numeric Precision Comparisons — Exact Row Deduplication + IQR Outlier Flags

> Numeric Precision Comparisons — Exact Row Deduplication + 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).

Deduplicates rows and flags IQR-based outliers in supplied numeric comparison records (source_value vs transformed_value) for up to 200 rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-049?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/numeric-precision-comparisons-exact-row-deduplication-iqr-outlier-flags-0acc853a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_blm79ULzmcrJnSD7juiVd

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 numeric-precision-comparisons-exact-row-deduplication-iqr-outlier-flags-0acc853a -d '<json body>'
```

Example prompt: Can you deduplicate these rows and flag IQR outliers across my source_value field? I have up to 50 records with row IDs, dataset groups, dates, and both source and transformed numeric values — I need the two-report analysis.

## When to prefer this

Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) batch analysis that combines exact duplicate detection with IQR-based outlier flagging on numeric source/transformed value pairs — especially in ETL, data reconciliation, or QA pipelines where you want two independent reports without any external API calls, ML predictions, or professional assessments.

## Known failure modes

- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) causes validation failure
- Invalid date format (not YYYY-MM-DD) rejected by pattern constraint
- Numeric values outside ±1,000,000,000,000 range rejected
- Empty rows array (minItems: 1) returns error
- Payment failure via x402 protocol blocks request

## How this service works

Numeric precision comparisons — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags for supplied numeric precision comparisons records (source_value, transformed_value). 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) an exact row deduplication report identifying which of the up to 200 submitted rows are duplicates, and (2) an IQR outlier flagging report marking which rows have source_value or transformed_value entries that fall outside the interquartile range. No external lookups or predictions are made — all analysis is local.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-exact-row-deduplication-iqr-outlier-flags-0acc853a/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)