# Trade Observations — Numeric Distribution + Date by Category Pivot

> Trade Observations — Numeric Distribution + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).

Computes numeric distribution statistics and a date-by-category pivot table for trade observation records (export_amount, import_amount) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-06-083?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/trade-observations-numeric-distribution-date-by-category-pivot-19faa361
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_-torxB1V9sEuoVDV2y4TC

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 trade-observations-numeric-distribution-date-by-category-pivot-19faa361 -d '<json body>'
```

Example prompt: I have 4 trade records — row-1 on 2026-10-01 for group-a with export 10 and import 1, row-2 on 2026-10-02 for group-b with export 20 and import 2, row-3 on 2026-10-03 for group-a with export 15 and import 3, and row-4 on 2026-10-04 for group-b with export 30 and import 4 — can you run both a numeric distribution report and a date-by-category pivot on the export_amount field?

## When to prefer this

Choose this endpoint when you have pre-collected trade observation data (up to 200 rows) and need both a numeric distribution breakdown and a date-by-category pivot in a single low-cost call ($0.01 USDC). It is ideal for economics or trade analysts who want offline, deterministic statistical summaries without any live data lookup, forecasting, or external enrichment. Prefer it over general analytics APIs when your data is already structured with region, date, export_amount, and import_amount fields.

## Known failure modes

- Fewer than 1 row supplied — validation error
- More than 200 rows supplied — request rejected
- Missing required fields (row_id, region, date, export_amount, import_amount) on any row — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern mismatch error
- Numeric values outside ±1,000,000,000,000 range — validation error
- Invalid field selector (not export_amount or import_amount) — enum validation error
- Payment not provided or insufficient USDC — 402 payment required

## How this service works

Trade observations — Numeric distribution + Date by category pivot: Numeric distribution + Date by category pivot for supplied trade observations records (export_amount, import_amount). 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 numeric distribution summary (e.g. min, max, mean, percentiles, histogram-style buckets) for the selected field (export_amount or import_amount), and (2) a date-by-category pivot table showing values broken down by date and region category — all computed locally from the supplied rows with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/trade-observations-numeric-distribution-date-by-category-pivot-19faa361/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)