# Data Ingestion Batches — Date×Category Pivot + Missing-Value Fill

> Data Ingestion Batches — Date×Category Pivot + 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).

Pivots ingestion batch records (received_rows, accepted_rows) by date and dataset_group, then fills missing values using zero, mean, or median imputation — returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-189?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-date-category-pivot-missing-value-fill-ce47edf7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Ys_VgNaYhqXjqjHWHA2ZZ

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-date-category-pivot-missing-value-fill-ce47edf7 -d '<json body>'
```

Example prompt: I have ingestion batch records with received_rows and accepted_rows across dataset groups like 'group-a' and 'group-b' for dates in October 2026 — can you pivot them by date and category, and fill any missing accepted_rows values using median imputation? Here are up to 50 rows of data.

## When to prefer this

Choose this endpoint when you have tabular ingestion batch records with received_rows and accepted_rows and need both a date×category pivot and missing-value imputation in a single $0.01 call. It is ideal for data engineers who want quick local reshaping and gap-filling of ETL metrics without sending data to an external analytics platform. Prefer it over general-purpose BI tools when you need a lightweight, pay-per-call operation on up to 200 rows with no infrastructure setup.

## Known failure modes

- Fewer than 1 row or more than 200 rows submitted — request rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation error
- Missing required fields (row_id, dataset_group, date) cause per-row rejection
- Numeric values outside ±1,000,000,000,000 range are rejected
- Invalid enum for field (must be 'received_rows' or 'accepted_rows') or method (must be 'zero', 'mean', 'median') returns validation error
- Payment of 0.01 USDC not attached causes 402 response

## How this service works

Data ingestion batches — Date by category pivot + Explicit missing-value fill: Date by category pivot + 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 date-by-category pivot table for the selected field (received_rows or accepted_rows), and (2) the same dataset with missing values explicitly filled using the chosen method (zero, mean, or median). Both reports are computed locally from the supplied rows 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-date-category-pivot-missing-value-fill-ce47edf7/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)