# Transformation Throughput Analytics — Daily Sum Series & Missing-Value Fill

> Transformation Throughput Analytics — Daily Sum Series & Missing-Value Fill 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 daily sum time series and fills missing values for transformation throughput records (processed_rows, duration_seconds) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-145?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-missing-value-fill-8c8f7488
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_FcGFMaDfLzzr0voNBOHb2

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-missing-value-fill-8c8f7488 -d '<json body>'
```

Example prompt: Can you run a daily sum series on my transformation throughput records and fill any missing processed_rows values using median imputation? I have about 50 rows with dates and dataset groups ready to send.

## When to prefer this

Choose this endpoint when you need both a daily sum aggregation and missing-value imputation on transformation throughput data (processed_rows or duration_seconds) in a single call, for datasets up to 200 rows. It is ideal for lightweight, self-contained ETL analytics where no external data sources or predictions are needed — just local computation on supplied records.

## Known failure modes

- Input exceeds 200 rows — request rejected
- Missing required fields (row_id, date, processed_rows, duration_seconds) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema rejection
- field enum value not recognized — validation error
- method enum value not recognized — validation error
- All values null for selected field — fill report may be uninformative

## How this service works

Transformation throughput — Daily sum series + Explicit missing-value fill: Daily sum series + Explicit missing-value fill 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 series aggregating the selected field (processed_rows or duration_seconds) by date, and (2) an explicit missing-value fill report where nulls in the selected field are imputed using the chosen method (zero, mean, or median). Results are derived entirely from the supplied data with no 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-analytics-daily-sum-series-missing-value-fill-8c8f7488/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)