# Data Ingestion Batches — Two-Measure Correlation + Explicit Missing-Value Fill

> Data Ingestion Batches — Two-Measure Correlation + 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 2026-10-16).

Computes Pearson correlation between received_rows and accepted_rows across up to 200 data ingestion batch records, while filling missing values using zero, mean, or median imputation, and returns two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-184?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-ingestion-batches-two-measure-correlation-explicit-missing-value-e8d68cf5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_uQu-foqJs05oXhzDgLUwq

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-ingestion-batches-two-measure-correlation-explicit-missing-value-e8d68cf5 -d '<json body>'
```

Example prompt: Analyze the correlation between received_rows and accepted_rows across my 50 ingestion batch records — use median to fill any missing values — and give me two analytical reports.

## When to prefer this

Choose this endpoint when you have up to 200 data ingestion batch records with received_rows and accepted_rows metrics and need both missing-value imputation and a correlation analysis between those two measures in a single low-cost call. It is ideal for data engineers auditing ETL pipeline quality or acceptance rates without needing external data, predictions, or professional assessments.

## Known failure modes

- More than 200 rows submitted — request exceeds maxItems limit
- Missing required fields (row_id, date, dataset_group) on any row — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — rejected
- All values for one measure are null after imputation — correlation cannot be computed
- Payment of 0.01 USDC not included — 402 payment required response

## How this service works

Data ingestion batches — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied data ingestion batches records (received_rows, accepted_rows). 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

Two analytical reports covering: (1) Pearson correlation coefficient between received_rows and accepted_rows across the submitted batch records, and (2) the dataset with explicit missing-value fills applied using the chosen method (zero, mean, or median). Reports are computed locally from supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-ingestion-batches-two-measure-correlation-explicit-missing-value-e8d68cf5/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)