# Transformation Throughput Analytics — Daily Sum Series + IQR Outlier Flags

> Transformation Throughput Analytics — Daily Sum Series + IQR Outlier Flags 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 daily aggregated sums and IQR-based outlier flags for transformation throughput records (processed_rows, duration_seconds) across up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-140?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-daily-sum-series-iqr-outlier-flags-c2e5b8b7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_nQ0cNCgSdavaOPfx5lX1t

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-daily-sum-series-iqr-outlier-flags-c2e5b8b7 -d '<json body>'
```

Example prompt: Can you analyze my ETL pipeline data for the past week — I have about 50 rows with dates, dataset groups, processed_rows, and duration_seconds — and give me a daily sum series plus flag any outliers using IQR for the processed_rows field?

## When to prefer this

Choose this endpoint when you have raw transformation throughput records (processed_rows or duration_seconds) and need both a daily aggregated time series and statistical outlier detection in a single call, without requiring any external data sources or live lookups. Best suited for ETL monitoring, data engineering analytics, and pipeline QA workflows with up to 200 rows.

## Known failure modes

- Input rows exceed 200-item limit — request rejected
- Missing required fields (row_id, date, processed_rows, duration_seconds) — validation error
- Date strings not matching YYYY-MM-DD pattern — schema rejection
- All values null for chosen field — unable to compute IQR
- Too few data points to compute meaningful IQR (fewer than 4 rows)

## How this service works

Transformation throughput — Daily sum series + IQR outlier flags: Daily sum series + IQR outlier flags 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 daily sum time series aggregating the chosen field (processed_rows or duration_seconds) across all records per date, and (2) IQR-based outlier flags identifying which dates or rows fall outside the interquartile range bounds — all computed locally without external lookups.

## 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-analytics-daily-sum-series-iqr-outlier-flags-c2e5b8b7/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)