# Data Reconciliation — IQR Outlier Flags + Date by Category Pivot

> Data Reconciliation — IQR Outlier Flags + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Runs two local analytical reports on supplied data reconciliation records: IQR-based outlier detection and a date-by-category pivot table, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-178?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-reconciliation-iqr-outlier-flags-date-by-category-pivot-916819fa
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_NHw4efwEDpoaA4UCXQLLm

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 data-reconciliation-iqr-outlier-flags-date-by-category-pivot-916819fa -d '<json body>'
```

Example prompt: Run IQR outlier detection and a date-by-category pivot on my reconciliation records — here are up to 200 rows with row_id, dataset_group, date, source_total, and target_total — flag any outliers in the source_total field and give me both reports.

## When to prefer this

Choose this endpoint when you need both IQR-based outlier detection and a date-by-category pivot in a single low-cost call on reconciliation data (source_total vs target_total). Ideal for ETL validation, financial close checks, or data migration audits where privacy matters (no external lookups). Best when you have up to 200 structured rows and want two complementary analytical views for $0.01 USDC.

## Known failure modes

- Fewer than 1 row supplied — minimum row count not met
- More than 200 rows submitted — exceeds maximum row limit
- Missing required fields (row_id, dataset_group, date, source_total, target_total) on any row
- Date field does not match YYYY-MM-DD format — pattern validation failure
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — schema rejection
- Invalid field enum value (must be 'source_total' or 'target_total')

## How this service works

Data reconciliation — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot for supplied data reconciliation records (source_total, target_total). 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) IQR outlier flags identifying which rows have source_total or target_total values outside the interquartile range, and (2) a pivot table grouping totals by date and dataset_group category. All computation is local with no external data lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-reconciliation-iqr-outlier-flags-date-by-category-pivot-916819fa/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)