# Dataset Partition Sizes Analytics — Record Quality Audit, Exact Row Deduplication & Equal-Width Histogram

> Dataset Partition Sizes Analytics — Record Quality Audit, Exact Row Deduplication & Equal-Width Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).

Runs three independent analytical reports (record quality audit, exact row deduplication, and equal-width histogram) on user-supplied dataset partition size records containing row counts and file sizes.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-07-219?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-23
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/dataset-partition-sizes-analytics-record-quality-audit-exact-row-f001b675
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_DOaTt2uK5Xvw01Rc63FCk

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 dataset-partition-sizes-analytics-record-quality-audit-exact-row-f001b675 -d '<json body>'
```

Example prompt: Can you run the three-report analytics package on my dataset partition records — a quality audit, exact deduplication check, and a 10-bin histogram on row_count — for these 5 rows: [{"row_id":"p1","dataset_group":"sales","date":"2024-01-01","row_count":50000,"file_mb":120.5}, {"row_id":"p2","dataset_group":"sales","date":"2024-01-02","row_count":48000,"file_mb":115.2}, {"row_id":"p3","dataset_group":"events","date":"2024-01-01","row_count":50000,"file_mb":120.5}, {"row_id":"p4","dataset_group":"events","date":"2024-01-03","row_count":null,"file_mb":88.0}, {"row_id":"p5","dataset_group":"sales","date":"2024-01-04","row_count":62000,"file_mb":140.0}]?

## When to prefer this

Choose this endpoint when you need three simultaneous analytical reports (quality audit, deduplication, histogram) on dataset partition size records without any external data lookups or ML inference. It is purpose-built for row_count and file_mb fields with a structured schema, making it ideal for data engineering pipelines that need lightweight, reproducible, local-only analytics on up to 200 partition records in a single cheap call.

## Known failure modes

- Exceeds 200-row limit — request rejected with validation error
- Invalid date format (not YYYY-MM-DD) causes row-level validation failure
- bins parameter outside 1–30 range returns schema validation error
- Missing required fields (row_id, dataset_group, date, row_count, file_mb) causes item-level rejection
- Null values in the histogram target field may reduce histogram coverage
- Payment of 0.01 USDC not fulfilled — 402 response returned before processing

## How this service works

Dataset partition sizes — Record quality audit + Exact row deduplication + Equal-width histogram: Record quality audit + Exact row deduplication + Equal-width histogram for supplied dataset partition sizes records (row_count, file_mb). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Returns three independent analytical reports: (1) a record quality audit flagging nulls, out-of-range values, and format issues in the supplied rows; (2) an exact row deduplication report identifying identical records; and (3) an equal-width histogram over the selected numeric field (row_count or file_mb) with the specified number of bins, all computed locally without any external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "row_count",
     "file_mb"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "file_mb": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "row_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "file_mb": 1,
     "row_count": 10,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "file_mb": 2,
     "row_count": 20,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "file_mb": 3,
     "row_count": 15,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "file_mb": 4,
     "row_count": 30,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "row_count",
    "file_mb"
   ],
   "type": "string",
   "default": "row_count"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/dataset-partition-sizes-analytics-record-quality-audit-exact-row-f001b675/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)