# Save Files Analytics — Numeric Interval Filter + Explicit Missing-Value Fill

> Save Files Analytics — Numeric Interval Filter + Explicit 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 2026-10-30).

Filters save-file records by a numeric range on save_kb or write_ms, and fills missing values using zero, mean, or median imputation, returning up to 2 analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-game-13-135?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/save-files-analytics-numeric-interval-filter-explicit-missing-value-e102ff8b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_5AJ6oVjdgFie9ntqHDzbv

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 save-files-analytics-numeric-interval-filter-explicit-missing-value-e102ff8b -d '<json body>'
```

Example prompt: I have a set of game save file records with save_kb and write_ms values — some are null — and I want to filter them to only include rows where save_kb is between 0 and 100, filling any missing save_kb values using median imputation. Can you run both analytical reports on up to 200 rows and show me the results?

## When to prefer this

Choose this endpoint when you have game save file records (save_kb, write_ms) that need both range-based filtering and missing-value imputation in a single call. It is ideal for data cleaning pipelines targeting game telemetry or save-file analytics where you need up to 2 reports on up to 200 rows without requiring external data sources or live lookups.

## Known failure modes

- Rows with dates not matching YYYY-MM-DD pattern will fail schema validation
- Providing fewer than 1 or more than 200 rows returns an error
- Specifying a minimum greater than maximum may yield zero matching rows
- Null row_id or row_id exceeding 80 characters will be rejected
- Invalid method or field enum values will cause a validation error
- Numeric values outside ±1,000,000,000,000 are rejected

## How this service works

Save files — Numeric interval filter + Explicit missing-value fill: Numeric interval filter + Explicit missing-value fill for supplied save files records (save_kb, write_ms). 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 up to 2 analytical reports covering the filtered subset of rows (those whose selected numeric field falls within the specified minimum–maximum interval) and the imputed dataset where missing values in the chosen field have been replaced using the specified method (zero, mean, or median). Reports are computed locally with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "game_area",
     "date",
     "save_kb",
     "write_ms"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "save_kb": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "write_ms": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "game_area": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "save_kb": 10,
     "write_ms": 1,
     "game_area": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "save_kb": 20,
     "write_ms": 2,
     "game_area": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "save_kb": 15,
     "write_ms": 3,
     "game_area": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "save_kb": 30,
     "write_ms": 4,
     "game_area": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "save_kb",
    "write_ms"
   ],
   "type": "string",
   "default": "save_kb"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  },
  "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/save-files-analytics-numeric-interval-filter-explicit-missing-value-e102ff8b/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)