# Data Ingestion Batches — Trailing Mean Series + IQR Outlier Flags

> Data Ingestion Batches — Trailing Mean Series + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).

Computes trailing mean time series and IQR-based outlier flags for received_rows and accepted_rows fields in data ingestion batch records (up to 200 rows, 2 reports per call).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-149?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-ingestion-batches-trailing-mean-series-iqr-outlier-flags-3b1b7164
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_-pMUEeo-QkwfCV27Ezns4

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-iqr-outlier-flags-3b1b7164 -d '<json body>'
```

Example prompt: Can you run trailing mean and IQR outlier detection on these ingestion batch records — I have 120 rows with received_rows and accepted_rows per date, targeting the received_rows field with a window of 7?

## When to prefer this

Choose this endpoint when you need both a rolling/trailing mean trend and IQR outlier detection on ingestion batch metrics (received_rows or accepted_rows) in a single call, without any external data dependencies. It is purpose-built for data engineering and ETL quality use cases and provides two statistical reports per call at minimal cost, making it ideal for lightweight batch anomaly detection pipelines that operate on self-contained historical records.

## Known failure modes

- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — batch size limit exceeded
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) on any row
- Date values not matching YYYY-MM-DD format — pattern validation failure
- Window size outside 2–200 range — parameter validation error
- All numeric values null — insufficient data for statistical computation
- Payment not included or insufficient — x402 payment required at $0.01 USDC

## How this service works

Data ingestion batches — Trailing mean series + IQR outlier flags: Trailing mean series + IQR outlier flags 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 trailing mean time series computed over the specified window for the chosen field (received_rows or accepted_rows), and (2) per-row IQR-based outlier flags indicating which records fall outside the interquartile range. Both reports are derived entirely from 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"
  },
  "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-iqr-outlier-flags-3b1b7164/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)