# Job Listing Inventories — Two-Measure Correlation + Explicit Missing-Value Fill

> Job Listing Inventories — Two-Measure Correlation + Explicit 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 2026-10-23).

Computes Pearson/Spearman correlation between listing_count and duplicate_listings, and fills missing values in a chosen field using zero, mean, or median imputation — two independent analytical reports for up to 200 rows of job listing inventory data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-13-184?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-23
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/job-listing-inventories-two-measure-correlation-explicit-missing-0d7a59d1
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_tfr8Shd4M7e07hJolbB3L

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 job-listing-inventories-two-measure-correlation-explicit-missing-0d7a59d1 -d '<json body>'
```

Example prompt: I have up to 200 rows of job listing inventory data with listing_count and duplicate_listings columns — some values are null. Can you run a two-measure correlation between those two fields AND fill missing values in listing_count using median imputation? Here's the data as an array of rows with row_id, company_group, date, listing_count, and duplicate_listings.

## When to prefer this

Choose this endpoint when you need both a correlation analysis and missing-value imputation on job listing inventory data in a single, low-cost call ($0.01 USDC for both reports). It is ideal for offline batch processing of up to 200 rows where no live data lookup, prediction, or external integration is needed. Prefer this over generic analytics tools when the data specifically involves listing_count and duplicate_listings metrics and you want structured, reproducible statistical output without setting up a local analysis pipeline.

## Known failure modes

- Fewer than 1 row supplied — request rejected with validation error
- More than 200 rows submitted — exceeds maximum, request rejected
- Invalid date format in any row (must be YYYY-MM-DD) — validation error
- Unknown imputation method value outside zero/mean/median enum — error
- Both measure fields entirely null — correlation cannot be computed, report may return NaN or error
- Payment not included or insufficient — x402 payment required error

## How this service works

Job listing inventories — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied job listing inventories records (listing_count, duplicate_listings). 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 correlation report showing the statistical relationship (e.g. Pearson/Spearman coefficient) between listing_count and duplicate_listings across the supplied rows; (2) a missing-value fill report showing imputed values for the chosen field using the selected method (zero, mean, or median). Results are computed locally on the supplied data — no external lookups performed.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/job-listing-inventories-two-measure-correlation-explicit-missing-0d7a59d1/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)