# Research Task Completion — Numeric Distribution + Missing-Value Fill

> Research Task Completion — Numeric Distribution + 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 2026-10-21).

Analyzes up to 200 rows of research task completion records, producing a numeric distribution report and filling missing values in either completed_tasks or assigned_tasks using zero, mean, or median imputation.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-22-085?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/research-task-completion-numeric-distribution-missing-value-fill-8ee70fb2
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_x3KizJ6rveft8sROd8j-5

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 research-task-completion-numeric-distribution-missing-value-fill-8ee70fb2 -d '<json body>'
```

Example prompt: I have up to 200 rows of research task completion records with company_group, date, completed_tasks, and assigned_tasks fields — can you run a numeric distribution report on completed_tasks and fill any missing values using median imputation on that same field?

## When to prefer this

Choose this endpoint when you have a batch of up to 200 research task completion records (with completed_tasks and/or assigned_tasks numeric fields) and need both a statistical distribution summary and missing-value imputation in a single low-cost call ($0.01 USDC for both reports). Ideal when data is already in hand (no live lookup needed), you want offline analytical computation, and you need to choose a specific imputation strategy (zero, mean, or median). Prefer alternatives if you need outlier detection, time-series forecasting, or more than 200 rows.

## Known failure modes

- Rows array exceeds 200 items — request rejected or truncated
- Invalid date format (not YYYY-MM-DD) — schema validation error
- Missing required fields (row_id, company_group, date) — validation failure
- Invalid enum for field or method — schema error
- All values in target field are null — mean/median imputation may be undefined or return 0
- Empty rows array — error or empty report returned

## How this service works

Research task completion — Numeric distribution + Explicit missing-value fill: Numeric distribution + Explicit missing-value fill for supplied research task completion records (completed_tasks, assigned_tasks). 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 independent analytical reports: (1) a numeric distribution summary (e.g. min, max, mean, median, percentiles, histogram-like buckets) for the specified field (completed_tasks or assigned_tasks), and (2) an explicit missing-value fill report showing which rows had nulls and what values were imputed using the chosen method (zero, mean, or median). Covers up to 200 input rows with no external lookups or live data.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "company_group",
     "date",
     "completed_tasks",
     "assigned_tasks"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "company_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "assigned_tasks": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "completed_tasks": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "company_group": "group-a",
     "assigned_tasks": 1,
     "completed_tasks": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "company_group": "group-b",
     "assigned_tasks": 2,
     "completed_tasks": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "company_group": "group-a",
     "assigned_tasks": 3,
     "completed_tasks": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "company_group": "group-b",
     "assigned_tasks": 4,
     "completed_tasks": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "completed_tasks",
    "assigned_tasks"
   ],
   "type": "string",
   "default": "completed_tasks"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/research-task-completion-numeric-distribution-missing-value-fill-8ee70fb2/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)