# Numeric Precision Comparisons — String Normalisation + Equal-Width Histogram

> Numeric Precision Comparisons — String Normalisation + Equal-Width Histogram 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).

Analyzes numeric precision comparison data (source vs transformed values) by producing a string normalization report and an equal-width histogram, locally, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-031?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-string-normalisation-equal-width-c58d3ab3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_s0e3mOGMI0KKW-LsHj66C

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-string-normalisation-equal-width-c58d3ab3 -d '<json body>'
```

Example prompt: Can you run a string normalization and equal-width histogram analysis on these source vs transformed value pairs from group-a and group-b — use 10 bins and analyze the source_value field? I have about 50 rows dated between 2025-01-01 and 2025-03-31.

## When to prefer this

Choose this endpoint when you need offline/local statistical analysis of numeric precision differences between a source and a transformed column, particularly when you want both a normalization summary and a histogram in a single low-cost call. Ideal for ETL auditing, data quality checks, and ML feature validation pipelines where no external data enrichment or prediction is needed.

## Known failure modes

- More than 200 rows submitted — request rejected, maxItems limit exceeded
- Invalid date format not matching YYYY-MM-DD pattern — validation error
- Bins value outside 1–30 range — rejected with schema error
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) — validation failure
- All values null for the selected field — histogram may be empty or error
- Payment not completed — 402 response, endpoint not executed

## How this service works

Numeric precision comparisons — String normalisation + Equal-width histogram: String normalisation + Equal-width histogram 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 string normalization report and (2) an equal-width histogram with the specified number of bins, both computed locally from the supplied rows of source_value and transformed_value pairs. No external lookups or predictions are made.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "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-string-normalisation-equal-width-c58d3ab3/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)