# Join Coverage Analytics — Numeric Interval Filter + Date by Category Pivot

> Join Coverage Analytics — Numeric Interval Filter + 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 2026-10-23).

Filters join coverage rows (matched_rows or source_rows) by a numeric interval and produces a date-by-category pivot table, returning two analytical reports for up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-133?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/join-coverage-analytics-numeric-interval-filter-date-by-category-pivot-3585dbd1
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_lK97kXsyPhC5P4yVZ7K9T

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 join-coverage-analytics-numeric-interval-filter-date-by-category-pivot-3585dbd1 -d '<json body>'
```

Example prompt: Analyze my join coverage data — I have 4 rows with groups 'group-a' and 'group-b' across dates in October 2026, and I want to filter the matched_rows field to values between 10 and 30, then pivot the results by date and category.

## When to prefer this

Choose this endpoint when you have pre-collected join coverage records (matched_rows, source_rows) and need two local analytical reports — a numeric interval filter and a date-by-category pivot — without calling any external data source. Ideal for lightweight, low-cost ($0.01 USDC) on-demand analysis of up to 200 rows of ETL or data pipeline join metrics grouped by dataset category over time.

## Known failure modes

- Fewer than 1 row supplied — returns validation error
- More than 200 rows submitted — exceeds maxItems limit
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- minimum greater than maximum — may return empty filtered set with no error
- Null values in matched_rows or source_rows — nulls handled per schema but may reduce pivot accuracy
- Missing required fields (row_id, dataset_group, date) — schema validation error

## How this service works

Join coverage — Numeric interval filter + Date by category pivot: Numeric interval filter + Date by category pivot for supplied join coverage records (matched_rows, source_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 numeric interval-filtered subset of the supplied join coverage rows based on the chosen field (matched_rows or source_rows) and the min/max bounds, and (2) a date-by-category pivot table showing aggregated values broken down by date and dataset_group, all computed locally on the up-to-200 supplied rows without any external lookup.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "matched_rows",
     "source_rows"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "source_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "matched_rows": {
      "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",
     "source_rows": 1,
     "matched_rows": 10,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "source_rows": 2,
     "matched_rows": 20,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "source_rows": 3,
     "matched_rows": 15,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "source_rows": 4,
     "matched_rows": 30,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "matched_rows",
    "source_rows"
   ],
   "type": "string",
   "default": "matched_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/join-coverage-analytics-numeric-interval-filter-date-by-category-pivot-3585dbd1/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)