# Feature Availability Analytics: Trailing Mean Series + Equal-Width Histogram

> Feature Availability Analytics: Trailing Mean Series + Equal-Width Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).

Computes a trailing moving-average time series and an equal-width histogram over feature availability data (populated_features or expected_features) for up to 200 rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-148?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/feature-availability-analytics-trailing-mean-series-equal-width-2addc03f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_i99NUslLNua8PZhmUJMss

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 feature-availability-analytics-trailing-mean-series-equal-width-2addc03f -d '<json body>'
```

Example prompt: Can you run a trailing mean series and equal-width histogram on my feature availability data — I have 50 rows with populated_features and expected_features values by date, use a window of 5 and 10 bins, analyzing the populated_features field?

## When to prefer this

Choose this endpoint when you need both a time-smoothed trend view (trailing mean) and a frequency distribution (histogram) of feature availability or data completeness metrics in a single paid call. It is ideal for ML feature store monitoring, data quality audits, and completeness reporting where you have structured row-level records with populated and expected feature counts by date. Prefer this over general statistics endpoints when you specifically need histogram binning plus rolling mean on feature-availability-shaped data without requiring live data lookups or external enrichment.

## Known failure modes

- Fewer than 1 or more than 200 rows supplied — request rejected
- Window size larger than the number of data rows — may produce sparse or empty trailing mean
- Missing required fields (row_id, date, populated_features, expected_features) on any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Bins parameter outside 1–30 range — rejected
- All values null for the selected field — histogram and mean series may be empty or undefined
- Payment not received or insufficient USDC — 402 response

## How this service works

Feature availability — Trailing mean series + Equal-width histogram: Trailing mean series + Equal-width histogram for supplied feature availability records (populated_features, expected_features). 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

Two independent analytical reports: (1) a trailing mean time series showing the rolling average of the selected feature field (populated_features or expected_features) over the specified window, and (2) an equal-width histogram binning the feature values into the requested number of bins with frequency counts — both computed locally against the supplied row data, up to 200 rows.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "populated_features",
     "expected_features"
    ],
    "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
     },
     "expected_features": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "populated_features": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "expected_features": 1,
     "populated_features": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "expected_features": 2,
     "populated_features": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "expected_features": 3,
     "populated_features": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "expected_features": 4,
     "populated_features": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "populated_features",
    "expected_features"
   ],
   "type": "string",
   "default": "populated_features"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/feature-availability-analytics-trailing-mean-series-equal-width-2addc03f/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)