# Transformation Throughput Analytics: Numeric Interval Filter + Date by Category Pivot

> Transformation Throughput 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 2026-10-28).

Applies a numeric interval filter and a date-by-category pivot to up to 200 transformation throughput records (processed_rows, duration_seconds), returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-133?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transformation-throughput-analytics-numeric-interval-filter-date-by-be89897f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_sKlDvADq8u6nrs57H-Vk0

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 transformation-throughput-analytics-numeric-interval-filter-date-by-be89897f -d '<json body>'
```

Example prompt: I have 150 transformation throughput records with processed_rows and duration_seconds — can you filter them to only include records where processed_rows is between 10 and 500, and also pivot the data by date and dataset_group so I can see category breakdowns?

## When to prefer this

Choose this endpoint when you have up to 200 transformation throughput records with processed_rows and duration_seconds fields and need both a numeric range filter and a date-by-category pivot in a single low-cost call. It is ideal for local, offline analytics on ETL or data pipeline run logs where no external lookup or prediction is needed. Prefer it over general analytics platforms when you want a cheap ($0.01 USDC), deterministic, dual-report output without setting up your own analytical engine.

## Known failure modes

- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds row limit
- Invalid date format (not YYYY-MM-DD) on any row — schema validation error
- Field value not in enum ['processed_rows','duration_seconds'] — schema validation error
- Minimum greater than maximum — may return empty filter result with no error
- Null values in numeric fields — nulls may be excluded from interval filter silently

## How this service works

Transformation throughput — Numeric interval filter + Date by category pivot: Numeric interval filter + Date by category pivot for supplied transformation throughput records (processed_rows, duration_seconds). 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

Two local analytical reports: (1) a numeric interval filter report listing transformation records where the chosen field (processed_rows or duration_seconds) falls within the specified minimum–maximum range, and (2) a date-by-category pivot table aggregating the throughput metrics by date and dataset_group. No external data is fetched; all computation runs on the supplied rows.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "processed_rows",
     "duration_seconds"
    ],
    "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
     },
     "processed_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "duration_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "processed_rows": 10,
     "duration_seconds": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "processed_rows": 20,
     "duration_seconds": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "processed_rows": 15,
     "duration_seconds": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "processed_rows": 30,
     "duration_seconds": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "processed_rows",
    "duration_seconds"
   ],
   "type": "string",
   "default": "processed_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/transformation-throughput-analytics-numeric-interval-filter-date-by-be89897f/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)