# Null Coverage Daily Sum Series — Missing-Value Fill Analytics

> Null Coverage Daily Sum Series — Missing-Value Fill Analytics is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-10).

Runs two local analytical reports on user-supplied daily null-coverage data: a daily sum time series and an explicit missing-value fill (zero, mean, or median) for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-145?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-10
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/null-coverage-daily-sum-series-missing-value-fill-analytics-83c49f9a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_nKqdl591JZg3suiyBIl9U

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-daily-sum-series-missing-value-fill-analytics-83c49f9a -d '<json body>'
```

Example prompt: I have 4 rows of daily data for October 2026 — group-a and group-b — with missing_values and total_values columns. Can you run the null coverage daily sum series and fill any missing values using the median method on the missing_values field?

## When to prefer this

Choose this endpoint when you have pre-collected daily time series data with null/missing value counts and need both a daily aggregate sum series and a filled dataset (zero, mean, or median imputation) in a single low-cost call. It is ideal for data quality audits, ETL validation, and offline analytics on up to 200 rows of grouped daily records where no live data lookup or external prediction is needed.

## Known failure modes

- More than 200 rows submitted — request rejected due to row limit
- Missing required fields (row_id, date, missing_values, total_values) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Field or method enum value not recognized — rejected with validation error
- Null or out-of-range numeric values exceeding ±1,000,000,000,000 — rejected
- Empty rows array — minimum 1 item required

## How this service works

Null coverage — Daily sum series + Explicit missing-value fill: Daily sum 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 daily sum series aggregating the specified field over the supplied date range, and (2) an explicit missing-value fill report where nulls in the target field are replaced using the chosen method (zero, mean, or median). Results 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/null-coverage-daily-sum-series-missing-value-fill-analytics-83c49f9a/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)