# Data Pipeline Runs — Explicit Missing-Value Fill

> Data Pipeline Runs — 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 2026-10-18).

Fills missing numeric values (processed_rows or rejected_rows) in up to 200 data pipeline run records using zero, mean, or median imputation.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ar-analytics-pipeline-runs-fill-missing?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-pipeline-runs-explicit-missing-value-fill-2dd9802a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_rV4HpbYn6tKmBteo0IJxs

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 data-pipeline-runs-explicit-missing-value-fill-2dd9802a -d '<json body>'
```

Example prompt: I have up to 200 data pipeline run records with some missing processed_rows values — can you fill those nulls using the median method across pipelines like group-a and group-b with dates like 2026-10-01?

## When to prefer this

Use this endpoint when you have up to 200 pipeline run records with null numeric fields and need a fast, local imputation (zero, mean, or median) without any external data enrichment or forecasting. Prefer it over general-purpose data cleaning tools when your data is specifically structured as pipeline run records (processed_rows, rejected_rows per pipeline per date) and you need a bounded, auditable fill report at low cost ($0.01 USDC).

## Known failure modes

- Empty or malformed rows array (minItems:1 not met)
- rows array exceeds 200 items (maxItems:200 exceeded)
- Invalid date format (must match YYYY-MM-DD pattern)
- row_id missing or exceeds 80 characters
- Invalid field enum value (must be processed_rows or rejected_rows)
- Invalid method enum value (must be zero, mean, or median)
- Numeric values outside allowed range (-1e12 to 1e12)
- Payment failure or insufficient USDC balance

## How this service works

Data pipeline runs - Explicit missing-value fill: Explicit missing-value fill for Data pipeline runs. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded explicit missing-value fill report.

## Output

A bounded missing-value fill report containing the input pipeline run records with null numeric values (processed_rows or rejected_rows) replaced using the chosen method (zero, mean, or median). The output includes the corrected records and descriptive analytics computed locally without external enrichment or forecasting.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "pipeline",
     "date",
     "processed_rows",
     "rejected_rows"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "pipeline": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "rejected_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "processed_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "pipeline": "group-a",
     "rejected_rows": 1,
     "processed_rows": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "pipeline": "group-b",
     "rejected_rows": 2,
     "processed_rows": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "pipeline": "group-a",
     "rejected_rows": 3,
     "processed_rows": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "pipeline": "group-b",
     "rejected_rows": 4,
     "processed_rows": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "processed_rows",
    "rejected_rows"
   ],
   "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/data-pipeline-runs-explicit-missing-value-fill-2dd9802a/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)