# Numeric Precision Comparisons — Row Ordering & Missing-Value Fill

> Numeric Precision Comparisons — Row Ordering & 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 2026-10-15).

Sorts numeric rows and fills missing values (zero, mean, or median) for source_value/transformed_value pairs across up to 200 supplied records, producing 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-124?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-row-ordering-missing-value-fill-ef30367e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ZeFtzOY7MD39QgUaDvrRZ

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-row-ordering-missing-value-fill-ef30367e -d '<json body>'
```

Example prompt: I have 4 rows of source and transformed values — some nulls included — can you sort them numerically by source_value and fill any missing entries using median imputation? Rows: row-1 group-a 2026-10-01 source=10 transformed=null, row-2 group-b 2026-10-02 source=20 transformed=2, row-3 group-a 2026-10-03 source=null transformed=3, row-4 group-b 2026-10-04 source=30 transformed=4.

## When to prefer this

Choose this endpoint when you have up to 200 rows of paired numeric values (source and transformed) and need both ordered ranking and explicit null imputation in a single call for $0.01 USDC. It is purpose-built for numeric precision comparison workflows — ideal for ETL QA, data transformation validation, or pre-processing checks — and delivers two bundled reports without any external data fetching or ML inference overhead.

## Known failure modes

- More than 200 rows submitted — request rejected at maxItems limit
- Invalid date format (not YYYY-MM-DD) — schema validation error
- source_value or transformed_value outside allowed range (-1T to +1T) — validation failure
- Unrecognized fill method or field enum value — schema rejection
- Empty rows array (minItems=1 not met) — validation error
- Payment not included or insufficient USDC — x402 payment required error

## How this service works

Numeric precision comparisons — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill 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

Returns 2 analytical reports covering: (1) rows sorted in numeric order by the specified field, and (2) missing values in that field explicitly filled using the chosen method (zero, mean, or median). Output is scoped to the supplied data only — no external lookups or predictions.

## 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-row-ordering-missing-value-fill-ef30367e/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)