# Data Ingestion Batches — Trailing Mean Series + Explicit Missing-Value Fill

> Data Ingestion Batches — Trailing Mean Series + 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 2026-10-21).

Computes a trailing mean time series and fills missing values in data ingestion batch records (received_rows, accepted_rows) for up to 200 rows, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-154?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-ingestion-batches-trailing-mean-series-explicit-missing-value-fill-7a125fcc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_P1kC16ro5RCLrKgDyh5GM

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-trailing-mean-series-explicit-missing-value-fill-7a125fcc -d '<json body>'
```

Example prompt: Can you run a trailing mean series with a window of 3 on the received_rows field for my ingestion batch records, filling any missing values using the mean method? Here's my data: row-1 on 2024-01-01 group-a got 100 received and 90 accepted, row-2 on 2024-01-02 group-a got null received and 85 accepted, row-3 on 2024-01-03 group-a got 110 received and 95 accepted.

## When to prefer this

Choose this endpoint when you need both a trailing/rolling mean time series AND missing-value imputation for data ingestion batch metrics (received_rows or accepted_rows) in a single paid call. It is purpose-built for ETL and pipeline monitoring use cases with structured daily batch records and delivers two reports at once. Prefer it over generic analytics tools when your data fits the ingestion batch schema and you want local analytical computation without external data lookups or prediction.

## Known failure modes

- Fewer than 1 or more than 200 rows supplied — request rejected
- Invalid date format (must be YYYY-MM-DD) — validation error
- Window size outside 2–200 range — rejected
- Field value not 'received_rows' or 'accepted_rows' — enum validation error
- Missing required row fields (row_id, dataset_group, date) — schema error
- Numeric values outside ±1,000,000,000,000 range — rejected
- Payment of 0.01 USDC not supplied — 402 payment required

## How this service works

Data ingestion batches — Trailing mean series + Explicit missing-value fill: Trailing mean series + 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 2 analytical reports: (1) a trailing mean time series computed over the specified window for the chosen field (received_rows or accepted_rows), and (2) an explicit missing-value fill report showing imputed values using the chosen method (zero, mean, or median). All computed locally against the supplied rows, 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-ingestion-batches-trailing-mean-series-explicit-missing-value-fill-7a125fcc/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)