# Null Coverage Analytics: Base-100 Series + Missing-Value Fill

> Null Coverage Analytics: Base-100 Series + 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 2026-10-14).

Computes a Base-100 indexed time series and fills missing values (zero, mean, or median) for supplied null-coverage records, producing 2 analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-169?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-base-100-series-missing-value-fill-ab983ed2
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_D1fUfLCyhOPg2zMYClJUg

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-base-100-series-missing-value-fill-ab983ed2 -d '<json body>'
```

Example prompt: I have a dataset with missing_values and total_values per row across two groups over several dates — can you build a Base-100 indexed series starting at row index 0 and fill any missing_values using median imputation? Here are up to 200 rows: group-a on 2026-10-01 has 10 missing out of 1 total, group-b on 2026-10-02 has 20 missing out of 2 total, group-a on 2026-10-03 has 15 missing out of 3 total.

## When to prefer this

Choose this endpoint when you need both a Base-100 indexed time series and explicit missing-value imputation (zero, mean, or median) computed together in a single call on up to 200 rows of null-coverage data. It is ideal for offline/batch data quality analysis where no live data lookup or external prediction is needed and cost must be minimal ($0.01 USDC for 2 reports).

## Known failure modes

- Rows array is empty or exceeds 200 items — validation error
- missing_values or total_values outside allowed numeric range (±1 trillion) — rejected
- date field does not match YYYY-MM-DD pattern — schema validation failure
- base_index out of range (0–199) — error
- field or method enum value not recognized — schema rejection
- Payment of 0.01 USDC not provided — 402 payment required

## How this service works

Null coverage — Base-100 series + Explicit missing-value fill: Base-100 series + Explicit missing-value fill 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 Base-100 normalized time series indexed from the specified base_index row, and (2) an explicit missing-value-filled dataset where nulls in the chosen field are replaced using the selected method (zero, mean, or median). Both reports are computed locally from the supplied data 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/null-coverage-analytics-base-100-series-missing-value-fill-ab983ed2/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)