# Numeric Precision Comparisons — Exact Row Deduplication + Trailing Mean Series

> Numeric Precision Comparisons — Exact Row Deduplication + Trailing Mean Series 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).

Performs exact row deduplication and trailing moving-average computation on numeric source/transformed value pairs for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-045?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-trailing-mean-b2c7e0a1
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Kp3o1Pk2AxyXH6oeHxhXi

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-trailing-mean-b2c7e0a1 -d '<json body>'
```

Example prompt: I have 150 rows of source vs transformed numeric values across two groups — can you run exact row deduplication and a trailing mean series with a window of 5 on the source_value field? Each row has a row_id, dataset_group, and date.

## When to prefer this

Choose this endpoint when you need both exact row deduplication and trailing moving-average analysis on a set of numeric source/transformed value pairs in a single call. It is ideal for data quality auditing of transformation pipelines, ETL validation, or any scenario where you have paired numeric records and want to identify redundancy while also computing smoothed trends — all without needing an external data connection or prediction service.

## Known failure modes

- Fewer than 1 row supplied — rejected by minItems constraint
- More than 200 rows supplied — rejected by maxItems constraint
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- source_value or transformed_value outside [-1e12, 1e12] range — rejected
- window value less than 2 or greater than 200 — schema validation failure
- field value not one of 'source_value' or 'transformed_value' — enum validation failure
- Missing required fields (row_id, dataset_group, date) — rejected

## How this service works

Numeric precision comparisons — Exact row deduplication + Trailing mean series: Exact row deduplication + Trailing mean series 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 two independent analytical reports: (1) an exact row deduplication report identifying fully duplicated rows across the supplied dataset, and (2) a trailing mean series computed over the specified field using the given window size, covering up to 200 input rows.

## 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-exact-row-deduplication-trailing-mean-b2c7e0a1/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)