# Data Ingestion Batches — Adjacent Row Changes + Explicit Missing-Value Fill

> Data Ingestion Batches — Adjacent Row Changes + 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).

Analyzes up to 200 data ingestion batch records, computing adjacent row changes and filling missing values using a chosen method (zero, mean, or median) for received_rows or accepted_rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-162?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-adjacent-row-changes-explicit-missing-value-fill-93af86ca
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_o09xSbCFekQ_TH5hAtx6L

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-adjacent-row-changes-explicit-missing-value-fill-93af86ca -d '<json body>'
```

Example prompt: For my ingestion batch records across group-a and group-b from 2026-10-01 to 2026-10-04, run the adjacent row changes report and fill any missing values in received_rows using the median method — here are the 4 rows with row_id, dataset_group, date, received_rows, and accepted_rows.

## When to prefer this

Choose this endpoint when you need both adjacent row-change analysis and missing-value imputation for ingestion batch metrics in a single call. It is ideal for small-to-medium datasets (up to 200 rows) where you want offline, reproducible computation on supplied data without sending data to an external model or live lookup service. Prefer it over general-purpose analytics when your data is structured around data ingestion pipeline metrics (received_rows, accepted_rows) grouped by dataset and date.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) cause schema rejection
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Numeric values outside ±1,000,000,000,000 are rejected
- Invalid enum values for field or method return a 400-level error
- Payment failure via x402 prevents execution

## How this service works

Data ingestion batches — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + 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 for the supplied ingestion batch rows: (1) an adjacent row changes report showing period-over-period differences in the selected field (received_rows or accepted_rows), and (2) an explicit missing-value fill report where nulls in the selected field are replaced using the specified method (zero, mean, or median). Both reports are computed locally on the 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-adjacent-row-changes-explicit-missing-value-fill-93af86ca/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)