# Null Coverage Analytics: Exact Row Deduplication + Date-by-Category Pivot

> Null Coverage 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 2026-10-14).

Analyzes up to 200 null-coverage records by performing exact row deduplication and a date-by-category pivot on missing_values or total_values fields, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-052?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/null-coverage-analytics-exact-row-deduplication-date-by-category-pivot-b5c958f3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_pxQN50Z8BIsLdwnisGpzU

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 null-coverage-analytics-exact-row-deduplication-date-by-category-pivot-b5c958f3 -d '<json body>'
```

Example prompt: I have 4 rows of null coverage data across two groups — row-1 (group-a, 2026-10-01, missing=10, total=1), row-2 (group-b, 2026-10-02, missing=20, total=2), row-3 (group-a, 2026-10-03, missing=15, total=3), row-4 (group-b, 2026-10-04, missing=30, total=4) — can you deduplicate them and give me a date-by-category pivot on the missing_values field?

## When to prefer this

Choose this endpoint when you need both exact row deduplication and a date-by-category pivot on null coverage data (missing_values and total_values) in a single low-cost call. Ideal for data quality workflows where you want to clean duplicate records and immediately summarize null rates across groups and dates without any external API calls, predictions, or live data lookups. Best suited for datasets up to 200 rows.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) cause schema rejection
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array is rejected (minItems: 1)
- Invalid field enum value (not 'missing_values' or 'total_values') causes an error

## How this service works

Null coverage — Exact row deduplication + Date by category pivot: Exact row deduplication + Date by category pivot for supplied null coverage records (missing_values, total_values). 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: (1) an exact row deduplication report identifying and removing duplicate records from the submitted null coverage rows, and (2) a date-by-category pivot table summarizing the chosen field (missing_values or total_values) broken down by date and dataset_group — all computed locally with no external data lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/null-coverage-analytics-exact-row-deduplication-date-by-category-pivot-b5c958f3/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)