# Recovery Objectives Numeric Row Ordering + Explicit Missing-Value Fill

> Recovery Objectives 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 2026-11-01).

Orders rows numerically by date and fills missing values (zero, mean, or median) in target_minutes or observed_minutes fields of recovery objectives records, returning 2 analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-security-20-124?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-01
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/recovery-objectives-numeric-row-ordering-explicit-missing-value-fill-bc7219a7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_CFoCT5kiZimupVS07GDLa

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 recovery-objectives-numeric-row-ordering-explicit-missing-value-fill-bc7219a7 -d '<json body>'
```

Example prompt: I have a dataset of recovery objective records with target_minutes and observed_minutes — some values are null — can you sort them by date and fill the missing target_minutes values using median imputation? I have about 50 rows across two control groups.

## When to prefer this

Choose this endpoint when you need a cheap ($0.01 USDC), offline, deterministic cleaning pass on recovery objectives records — specifically when you need both date-ordered row sorting and explicit null imputation (zero, mean, or median) on target_minutes or observed_minutes fields, and you want two bundled analytical reports out of the same call. Prefer this over general data cleaning tools when your data is specifically structured as recovery objective records with control groups and date-stamped minute measurements.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, target_minutes, observed_minutes) cause schema rejection
- Invalid date format (not YYYY-MM-DD) fails pattern validation
- Unsupported fill method or field enum value returns an error
- Empty rows array rejected due to minItems:1 constraint

## How this service works

Recovery objectives — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied recovery objectives records (target_minutes, observed_minutes). 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 2 analytical reports covering the supplied recovery objectives records after numerically ordering rows by date and explicitly filling missing values in the selected field (target_minutes or observed_minutes) using the chosen method (zero, mean, or median). Reports are generated 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",
     "control_group",
     "date",
     "target_minutes",
     "observed_minutes"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "control_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "target_minutes": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "observed_minutes": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "control_group": "group-a",
     "target_minutes": 10,
     "observed_minutes": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "control_group": "group-b",
     "target_minutes": 20,
     "observed_minutes": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "control_group": "group-a",
     "target_minutes": 15,
     "observed_minutes": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "control_group": "group-b",
     "target_minutes": 30,
     "observed_minutes": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "target_minutes",
    "observed_minutes"
   ],
   "type": "string",
   "default": "target_minutes"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/recovery-objectives-numeric-row-ordering-explicit-missing-value-fill-bc7219a7/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)