# Data Ingestion Batches — Grouped Numeric Summary + Explicit Missing-Value Fill

> Data Ingestion Batches — Grouped Numeric Summary + 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).

Computes a grouped numeric summary and fills missing values (zero/mean/median) for up to 200 data ingestion batch records across received_rows and accepted_rows fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-099?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-ingestion-batches-grouped-numeric-summary-explicit-missing-value-4b8cb885
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VmUkwePNWFBaqmpaPMSOA

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-grouped-numeric-summary-explicit-missing-value-4b8cb885 -d '<json body>'
```

Example prompt: Can you summarize my data ingestion batch records by dataset group and fill any missing accepted_rows values using the median? I have up to 50 rows with fields like row_id, dataset_group, date, received_rows, and accepted_rows.

## When to prefer this

Choose this endpoint when you have a batch of data ingestion records (up to 200 rows) with received_rows and accepted_rows metrics and need both a grouped statistical summary by dataset group AND explicit missing-value imputation in a single call. It is especially suited for data engineering teams monitoring ETL pipeline quality without needing external data sources or real-time lookups. Prefer this over general analytics tools when cost-efficiency matters ($0.01 USDC for two reports) and the data is already structured with the required schema fields.

## Known failure modes

- More than 200 rows submitted — request exceeds the maxItems limit and will be rejected
- Missing required fields (row_id, dataset_group, date, received_rows, or accepted_rows) on any row causes validation failure
- Invalid date format (not YYYY-MM-DD) triggers schema validation error
- Numeric values outside the ±1,000,000,000,000 range are rejected
- Invalid fill method or field enum value causes a bad request error
- Empty rows array (minItems: 1 violated) returns an error

## How this service works

Data ingestion batches — Grouped numeric summary + Explicit missing-value fill: Grouped numeric summary + 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

Returns two analytical reports: (1) a grouped numeric summary of the chosen field (received_rows or accepted_rows) broken down by dataset_group, and (2) the same dataset with missing values explicitly filled using the selected method (zero, mean, or median). Both reports operate on up to 200 supplied rows 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",
     "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-grouped-numeric-summary-explicit-missing-value-4b8cb885/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)