# Transformation Throughput Analytics — Numeric Distribution + Missing-Value Fill

> Transformation Throughput Analytics — Numeric Distribution + 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 2026-10-28).

Computes numeric distribution statistics and fills missing values (zero/mean/median) for transformation throughput records (processed_rows, duration_seconds) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-085?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transformation-throughput-analytics-numeric-distribution-missing-d57c2722
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_n9r360VZq4bl0wStJ1Ngf

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 transformation-throughput-analytics-numeric-distribution-missing-d57c2722 -d '<json body>'
```

Example prompt: Can you run a numeric distribution analysis and fill in any missing processed_rows values using median imputation on these ETL records — I have about 50 rows with date, dataset_group, processed_rows, and duration_seconds fields?

## When to prefer this

Choose this endpoint when you have up to 200 transformation throughput records (ETL/pipeline data) and need both a numeric distribution summary and missing-value imputation in a single low-cost ($0.01 USDC) call. Ideal for lightweight, local analytical tasks on processed_rows or duration_seconds without needing a full analytics platform or live data connection.

## Known failure modes

- More than 200 rows submitted — request rejected at maxItems limit
- Invalid date format (not YYYY-MM-DD) causes schema validation error
- Unknown fill method or field enum value causes rejection
- All values missing for chosen field — mean/median imputation may be undefined
- Numeric values outside allowed range cause validation failure

## How this service works

Transformation throughput — Numeric distribution + Explicit missing-value fill: Numeric distribution + Explicit missing-value fill for supplied transformation throughput records (processed_rows, duration_seconds). 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 analytical reports: (1) a numeric distribution summary (e.g. min, max, mean, percentiles, histogram buckets) for the specified field, and (2) an explicit missing-value fill report showing imputed values using the chosen method (zero, mean, or median) — all computed locally without external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "processed_rows",
     "duration_seconds"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "processed_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "duration_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "processed_rows": 10,
     "duration_seconds": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "processed_rows": 20,
     "duration_seconds": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "processed_rows": 15,
     "duration_seconds": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "processed_rows": 30,
     "duration_seconds": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "processed_rows",
    "duration_seconds"
   ],
   "type": "string",
   "default": "processed_rows"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-analytics-numeric-distribution-missing-d57c2722/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)