# Data Ingestion Batches — Secondary-Measure Weighted Mean + Explicit Missing-Value Fill

> Data Ingestion Batches — Secondary-Measure Weighted Mean + 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 2026-10-17).

Computes a secondary-measure weighted mean and fills missing values for up to 200 data ingestion batch records (received_rows, accepted_rows), returning two analytical reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-187?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-17
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-ingestion-batches-secondary-measure-weighted-mean-explicit-b18e4c65
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_9zeYkOgN56zKwhilK8It3

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-secondary-measure-weighted-mean-explicit-b18e4c65 -d '<json body>'
```

Example prompt: Can you compute a secondary-measure weighted mean for my data ingestion batches and fill any missing received_rows values using median imputation? I have up to 50 rows across two dataset groups — group-alpha and group-beta — dated from 2025-01-01 to 2025-01-10.

## When to prefer this

Choose this endpoint when you need both a weighted mean computation and explicit missing-value imputation on data ingestion batch records (received_rows/accepted_rows) in a single call. It is ideal for pipeline monitoring, data quality reporting, and batch analytics workflows where up to 200 rows need to be analyzed offline without external data lookups. Prefer this over general-purpose analytics tools when you want a low-cost ($0.01 USDC), deterministic, reproducible result from supplied data alone.

## Known failure modes

- More than 200 rows submitted — request exceeds maxItems limit and will be rejected
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) cause validation errors
- Invalid date format (must match YYYY-MM-DD pattern) results in schema validation failure
- Numeric values outside the allowed range (±1,000,000,000,000) are rejected
- Invalid enum value for 'field' or 'method' causes a bad request error
- Empty rows array (minItems:1 not satisfied) returns an error

## How this service works

Data ingestion batches — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + 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 per call: (1) a secondary-measure weighted mean computed over the supplied received_rows or accepted_rows field, grouped by dataset_group and date, and (2) an explicit missing-value fill report showing how null or absent values in the chosen field were imputed using the selected method (zero, mean, or median). Results are derived entirely from the supplied data — no external lookups or live data.

## 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-secondary-measure-weighted-mean-explicit-b18e4c65/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)