# Training Assessments — Numeric Row Ordering + Explicit Missing-Value Fill

> Training Assessments — Numeric Row Ordering + Explicit 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 2026-10-26).

Sorts training assessment rows numerically and fills missing pre_score or post_score values using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-11-124?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/training-assessments-numeric-row-ordering-explicit-missing-value-fill-5fb850cf
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ChgcARK2vNPRfC-U7ds3U

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 training-assessments-numeric-row-ordering-explicit-missing-value-fill-5fb850cf -d '<json body>'
```

Example prompt: I have training assessment records for two course groups with some missing pre_score values — can you sort all the rows numerically and fill in the missing pre_score entries using median imputation? Here are up to 200 rows with row_id, course_group, date, pre_score, and post_score fields.

## When to prefer this

Choose this endpoint when you need to both numerically order training assessment records and impute missing numeric scores (pre_score or post_score) in a single paid call, getting two structured reports back. Ideal for preprocessing education or training data before downstream analysis, especially when your dataset has up to 200 rows with null score entries and you want a deterministic fill method (zero, mean, or median) without involving any live prediction or external data sources.

## Known failure modes

- More than 200 rows submitted — exceeds maximum row limit
- Missing required fields (row_id, course_group, date, pre_score, post_score) on any row
- Invalid date format (must match YYYY-MM-DD pattern)
- Invalid method value outside enum (zero, mean, median)
- Invalid field value outside enum (pre_score, post_score)
- Empty rows array submitted
- Score values outside allowed numeric range (-1,000,000,000,000 to 1,000,000,000,000)

## How this service works

Training assessments — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied training assessments records (pre_score, post_score). 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) the assessment rows sorted in numeric order by row, and (2) the specified field (pre_score or post_score) with missing values explicitly filled using the chosen method (zero, mean, or median). Both reports are derived from the supplied data using local analytical engines with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/training-assessments-numeric-row-ordering-explicit-missing-value-fill-5fb850cf/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)