# Numeric Precision Comparisons — Base-100 Series + IQR Outlier Flags

> Numeric Precision Comparisons — Base-100 Series + 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).

Generates a base-100 indexed time series and IQR-based outlier flags for up to 200 rows of source/transformed numeric value pairs, producing two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-164?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-base-100-series-iqr-outlier-flags-346390f8
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_cjCLsnBsQ9rQKH9IwbE6J

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-base-100-series-iqr-outlier-flags-346390f8 -d '<json body>'
```

Example prompt: I have up to 200 rows of source and transformed numeric values by date and group — can you run a base-100 indexed series starting from row index 0 on the source_value field, and also flag any IQR outliers across my dataset?

## When to prefer this

Choose this endpoint when you need both a base-100 normalized index series and IQR outlier detection on a single dataset of up to 200 numeric rows in one call. It is best suited for data quality checks between original and transformed values, ETL validation, or exploratory statistical analysis where no external data, predictions, or live lookups are required. Prefer alternatives if you need more than 200 rows, real-time data enrichment, machine learning predictions, or professional assessments.

## Known failure modes

- Empty or missing rows array returns an error
- More than 200 rows submitted exceeds the maxItems limit and will be rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- base_index out of range (>=number of rows) may cause indexing errors
- All-null source_value or transformed_value columns may produce degenerate results
- Invalid field enum value (not 'source_value' or 'transformed_value') causes rejection

## How this service works

Numeric precision comparisons — Base-100 series + IQR outlier flags: Base-100 series + 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: (1) a base-100 indexed time series for the specified field, anchored at the given base_index row, showing relative change across all rows; and (2) IQR-based outlier flags identifying which rows contain statistically anomalous values. Results cover up to 200 input rows and are computed locally 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_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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-base-100-series-iqr-outlier-flags-346390f8/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)