# Save Files Analytics — Date×Category Pivot + Missing-Value Fill

> Save Files Analytics — Date×Category Pivot + 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).

Pivots save-file metrics (save_kb, write_ms) by date and game_area category, with explicit missing-value imputation using zero, mean, or median fill strategies.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-game-13-189?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-date-category-pivot-missing-value-fill-2fe7edcf
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_B4lk9sadhQsstNW3_tbNS

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-date-category-pivot-missing-value-fill-2fe7edcf -d '<json body>'
```

Example prompt: Pivot my game save file records by date and game_area — I have up to 50 rows with save_kb and write_ms values, some nulls — use median fill for the missing save_kb values.

## When to prefer this

Choose this endpoint when you have structured game save-file records (with save_kb and write_ms columns) and need a date-by-category pivot table with controlled missing-value imputation — particularly when your dataset has up to 200 rows and you want two simultaneous analytical views (pivot + fill) for a flat $0.01 fee without needing any external data sources or live lookups.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Unrecognized fill method value outside zero/mean/median enum
- Missing required fields (row_id, game_area, date) causes row rejection
- All values null for a field makes mean/median fill undefined — may default to zero
- Malformed numeric values outside allowed range rejected by schema

## How this service works

Save files — Date by category pivot + Explicit missing-value fill: Date by category pivot + 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 two analytical reports: (1) a date×game_area pivot table for the chosen metric field, and (2) the same dataset with explicit missing-value imputation applied using the selected fill method (zero, mean, or median). Covers up to 200 rows of supplied save file records with no external data 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/save-files-analytics-date-category-pivot-missing-value-fill-2fe7edcf/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)