# Business Event Participation — Numeric Interval Filter + Trailing Mean Series

> Business Event Participation — Numeric Interval Filter + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).

Filters business event participation rows by a numeric interval and computes a trailing mean time series for attendee_count or company_count, returning 2 analytical reports for up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-19-126?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/business-event-participation-numeric-interval-filter-trailing-mean-18b2f29c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_9uw_9jNHGiQzS91ifJoIJ

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 business-event-participation-numeric-interval-filter-trailing-mean-18b2f29c -d '<json body>'
```

Example prompt: I have 150 rows of business event participation data with attendee_count and company_count by date and group — can you filter rows where attendee_count is between 10 and 500, then compute a trailing mean series with a window of 7 using the attendee_count field?

## When to prefer this

Choose this endpoint when you have pre-collected business event participation data (up to 200 rows) and need both a numeric range filter and a trailing mean time series computed in a single call. It is ideal for smoothing event attendance trends, excluding outliers by numeric bounds, and getting two complementary analytical views in one low-cost operation. Prefer it over general-purpose analytics when your data fits the business event participation schema (attendee_count, company_count) and you need a fast, deterministic, no-side-effect computation without live data dependencies.

## Known failure modes

- Fewer than 1 or more than 200 rows supplied — request rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- Window size outside 2–200 range — validation error
- Minimum greater than maximum — may produce empty filtered result set
- Null values in the selected field — may affect trailing mean calculation
- Missing required row fields (row_id, company_group, date) — schema validation error

## How this service works

Business event participation — Numeric interval filter + Trailing mean series: Numeric interval filter + Trailing mean series for supplied business event participation records (attendee_count, company_count). 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 2 analytical reports per call: (1) a numeric interval-filtered subset of the supplied rows based on the specified field, minimum, and maximum thresholds; and (2) a trailing mean time series computed over the specified window size for the chosen field (attendee_count or company_count). All computation is performed locally on the supplied data — no external lookups or live data are used.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "company_group",
     "date",
     "attendee_count",
     "company_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "company_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "company_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "attendee_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "company_count": 1,
     "company_group": "group-a",
     "attendee_count": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "company_count": 2,
     "company_group": "group-b",
     "attendee_count": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "company_count": 3,
     "company_group": "group-a",
     "attendee_count": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "company_count": 4,
     "company_group": "group-b",
     "attendee_count": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "attendee_count",
    "company_count"
   ],
   "type": "string",
   "default": "attendee_count"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/business-event-participation-numeric-interval-filter-trailing-mean-18b2f29c/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)