# Numeric Precision Comparisons — Adjacent Row Changes + Date by Category Pivot

> Numeric Precision Comparisons — Adjacent Row Changes + 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 2026-10-15).

Runs two local analytical reports on up to 200 rows of numeric precision comparison data: adjacent row-to-row change analysis and a date-by-category pivot table, covering source_value and transformed_value fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-160?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-adjacent-row-changes-date-by-category-2f7b23bd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_oVb5VzX-v1rhCSOMUFEDq

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-adjacent-row-changes-date-by-category-2f7b23bd -d '<json body>'
```

Example prompt: I have a table of up to 200 rows with source_value and transformed_value measurements across different dataset groups and dates — can you run adjacent row change analysis and a date-by-category pivot on the source_value field for me?

## When to prefer this

Choose this endpoint when you have up to 200 rows of paired numeric data (source and transformed values) tagged with dates and group labels, and you need both sequential delta analysis and a date-by-category pivot in a single low-cost call. It is ideal for ETL validation, data transformation audits, or any scenario where you want two complementary analytical views on the same numeric precision dataset without external dependencies or live data lookups.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) on any row — validation error
- Date fields not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside ±1,000,000,000,000 range — schema rejection
- Empty rows array — minimum item count not met
- Invalid field enum value (must be source_value or transformed_value) — schema error

## How this service works

Numeric precision comparisons — Adjacent row changes + Date by category pivot: Adjacent row changes + Date by category pivot 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) adjacent row changes showing sequential numeric deltas between consecutive rows for the selected field, and (2) a date-by-category pivot table grouping the selected field's values by date and dataset_group. Results are computed locally from the supplied data with no external 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-adjacent-row-changes-date-by-category-2f7b23bd/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)