# Numeric Precision Comparisons Analytics — Grouped Summary & Category Frequencies

> Numeric Precision Comparisons Analytics — Grouped Summary & Category Frequencies 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 supplied numeric precision comparison records: a grouped numeric summary and category frequency counts, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-086?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-analytics-grouped-summary-category-abb4d20a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_hqudeqVor_tv3ipzRvyYM

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-analytics-grouped-summary-category-abb4d20a -d '<json body>'
```

Example prompt: Can you run a grouped numeric summary and category frequency report on my precision comparison data? I have 4 rows — row-1 in group-a on 2026-10-01 with source 10 and transformed 1, row-2 in group-b on 2026-10-02 with source 20 and transformed 2, row-3 in group-a on 2026-10-03 with source 15 and transformed 3, row-4 in group-b on 2026-10-04 with source 30 and transformed 4 — and I want to analyze the source_value field.

## When to prefer this

Choose this endpoint when you have up to 200 rows of numeric comparison records (with source and transformed value pairs tagged by group) and need both grouped descriptive statistics and category frequency counts in a single $0.01 call. It is ideal for lightweight, offline-style analytics on precision comparison or data transformation audit data without needing an external analytics platform or database query engine.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Numeric values outside ±1,000,000,000,000 range are rejected
- Empty rows array (minItems: 1 violated) causes error
- Invalid field enum value (not source_value or transformed_value) causes error

## How this service works

Numeric precision comparisons — Grouped numeric summary + Category frequencies: Grouped numeric summary + Category frequencies 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) a grouped numeric summary showing descriptive statistics (e.g. count, min, max, mean) for the selected field broken down by dataset_group, and (2) category frequency counts showing how often each dataset_group appears across the supplied rows. Both reports are computed locally with no external lookups, 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-analytics-grouped-summary-category-abb4d20a/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)