# Schema Conformity Analytics: Exact Row Deduplication + Date-by-Category Pivot

> Schema Conformity Analytics: Exact Row Deduplication + Date-by-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).

Deduplicates rows and produces a date-by-category pivot table for schema conformity metrics (valid_records, checked_records) across up to 200 rows in two bundled reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-052?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-analytics-exact-row-deduplication-date-by-category-1a05bed9
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_JqT26P4Wk6fiNFxr88d9J

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 schema-conformity-analytics-exact-row-deduplication-date-by-category-1a05bed9 -d '<json body>'
```

Example prompt: I have up to 200 rows of schema conformity data with fields row_id, dataset_group, date, valid_records, and checked_records — can you deduplicate the rows exactly and then pivot valid_records by date and dataset_group into a summary table?

## When to prefer this

Choose this endpoint when you need both exact row deduplication and a date-by-category pivot table for schema conformity data (valid_records / checked_records) in a single low-cost call. It is purpose-built for data quality audit workflows on datasets up to 200 rows and bundles two reports for $0.01 USDC, making it efficient for lightweight, offline analytical processing without requiring external lookup or ML inference.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, dataset_group, valid_records, checked_records) cause validation errors
- Malformed date strings not matching YYYY-MM-DD pattern will fail schema validation
- Null numeric values may affect pivot aggregation totals
- Empty rows array returns an error

## How this service works

Schema conformity — Exact row deduplication + Date by category pivot: Exact row deduplication + Date by category pivot for supplied schema conformity records (valid_records, checked_records). 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 deduplicated row set with exact duplicate rows removed, and (2) a date-by-category pivot table cross-tabulating the chosen metric (valid_records or checked_records) by date and dataset_group, covering up to 200 input rows.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-analytics-exact-row-deduplication-date-by-category-1a05bed9/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)