# Data Ingestion Batches — Numeric Interval Filter + Two-Measure Correlation

> Data Ingestion Batches — Numeric Interval Filter + Two-Measure Correlation 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).

Filters data ingestion batch records by a numeric interval and computes the correlation between received_rows and accepted_rows for up to 200 rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-131?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-numeric-interval-filter-two-measure-correlation-9db9e7fe
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_hEh_3kYiA9WHESE3atgS4

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-numeric-interval-filter-two-measure-correlation-9db9e7fe -d '<json body>'
```

Example prompt: I have ingestion batch records with received_rows and accepted_rows across multiple dataset groups — can you filter records where received_rows is between 5 and 50, and then compute the correlation between received_rows and accepted_rows across all 4 rows I'm sending you?

## When to prefer this

Choose this endpoint when you have up to 200 data ingestion batch records with received_rows and accepted_rows fields and need both interval-based filtering and a correlation analysis between those two measures in a single low-cost call ($0.01 USDC). It is ideal for pipeline QA, data quality monitoring, or acceptance rate analysis where you supply the data directly and want fast local computation without any external data lookup or live API dependency.

## Known failure modes

- Input array exceeds 200 rows — request is rejected
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) cause validation error
- Date values not matching YYYY-MM-DD pattern are rejected
- Numeric values outside ±1,000,000,000,000 bounds cause schema validation failure
- Empty rows array (minItems:1 not satisfied) causes rejection
- Minimum greater than maximum produces an empty filtered result set
- All null values for a measure prevents meaningful correlation computation

## How this service works

Data ingestion batches — Numeric interval filter + Two-measure correlation: Numeric interval filter + Two-measure correlation 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 independent analytical reports based on the supplied data: (1) the subset of ingestion batch records where the selected field falls within the specified numeric interval [minimum, maximum], and (2) a correlation analysis between received_rows and accepted_rows across the filtered or full dataset — computed entirely locally using shared analytical engines, with no external lookups or predictions.

## 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"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-ingestion-batches-numeric-interval-filter-two-measure-correlation-9db9e7fe/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)