# Null Coverage Analytics: String Normalisation + Trailing Mean Series

> Null Coverage Analytics: String Normalisation + 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 2026-10-14).

Computes string normalisation and trailing mean series reports for null coverage records (missing_values, total_values) across up to 200 rows using local analytical engines.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-028?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/null-coverage-analytics-string-normalisation-trailing-mean-series-960e7866
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_JIbtoFdae2KO1aFxhoYXr

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 null-coverage-analytics-string-normalisation-trailing-mean-series-960e7866 -d '<json body>'
```

Example prompt: Can you run a null coverage analysis on my dataset — I have 150 rows with missing_values and total_values per date, grouped by dataset_group, and I want both the string normalisation report and a trailing mean series using a window of 5 for the missing_values field?

## When to prefer this

Choose this endpoint when you need offline, local analytical computation on null coverage records — specifically when you want both a string normalisation report and a trailing mean series in a single call for up to 200 rows. Ideal for data quality monitoring pipelines that don't require live lookups, predictions, or external data enrichment. Best suited for structured tabular datasets with date-stamped rows grouped by dataset category.

## Known failure modes

- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows submitted — maximum is 200 rows
- Window size smaller than 2 or larger than 200 — invalid window parameter
- Date fields not matching YYYY-MM-DD pattern — schema validation failure
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) — request rejected
- field enum value not one of 'missing_values' or 'total_values' — validation error

## How this service works

Null coverage — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied null coverage records (missing_values, total_values). 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 string normalisation report describing the structure and normalized representation of the supplied null coverage records, and (2) a trailing mean series for the specified numeric field (missing_values or total_values) computed over the given rolling window — all processed locally with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/null-coverage-analytics-string-normalisation-trailing-mean-series-960e7866/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)