# Transformation Throughput Analytics — Base-100 Series + Two-Measure Correlation

> Transformation Throughput Analytics — Base-100 Series + Two-Measure Correlation 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).

Computes a Base-100 index series and a two-measure correlation report for transformation throughput records containing processed_rows and duration_seconds fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-165?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-base-100-series-two-measure-551fc17e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_XxEgpeT6S3CBHdMlGsKam

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-base-100-series-two-measure-551fc17e -d '<json body>'
```

Example prompt: I have a dataset of up to 150 ETL job records with columns row_id, dataset_group, date, processed_rows, and duration_seconds — can you compute a base-100 index series for processed_rows starting from row index 0, and also run a correlation report between processed_rows and duration_seconds?

## When to prefer this

Choose this endpoint when you need to index transformation throughput metrics (processed_rows, duration_seconds) to a base-100 scale and simultaneously measure their pairwise correlation — all from supplied data without any external lookups. Ideal for data engineering teams that want to benchmark ETL job performance relative to a reference row and understand whether processing volume and duration move together. Use this over generic statistics APIs when you specifically have pipeline throughput records in this exact schema and want two pre-packaged analytical outputs in one $0.01 call.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, processed_rows, duration_seconds) on any row causes validation failure
- base_index out of range (>= number of supplied rows) causes error
- Null values in the field chosen for base-100 indexing may produce undefined or partial results
- Malformed date strings not matching YYYY-MM-DD pattern will fail schema validation
- Zero value at the base_index row causes division-by-zero in the Base-100 calculation

## How this service works

Transformation throughput — Base-100 series + Two-measure correlation: Base-100 series + Two-measure correlation 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

Returns two analytical reports: (1) a Base-100 indexed series for the chosen field (processed_rows or duration_seconds), where the value at the specified base_index row equals 100 and all other values are scaled proportionally; and (2) a two-measure correlation report quantifying the statistical relationship between processed_rows and duration_seconds across the supplied rows. Results are computed locally from the supplied data only — no external lookups or predictions are performed.

## 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-analytics-base-100-series-two-measure-551fc17e/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)