# Save Files Daily Sum Series with Missing-Value Fill

> Save Files Daily Sum Series with 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).

Computes daily sum time series for save file metrics (save_kb or write_ms) and fills missing values using zero, mean, or median imputation — returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-game-13-145?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-daily-sum-series-with-missing-value-fill-aa415b49
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_tfPRr0QuPaI9bNvzL8YHW

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-daily-sum-series-with-missing-value-fill-aa415b49 -d '<json body>'
```

Example prompt: I have save file records for my game across two groups from October 1–4, 2026 with save_kb values — can you compute the daily sum series for save_kb and fill any missing values using median imputation?

## When to prefer this

Choose this endpoint when you need to aggregate save file performance data (save sizes in KB or write latencies in ms) into a daily sum time series and want explicit missing-value imputation built into the same call. Ideal for game analytics pipelines where save event logs contain nulls and you need clean daily totals without a separate ETL step. Not suitable for live lookups, predictions, or datasets larger than 200 rows per call.

## Known failure modes

- Fewer than 1 or more than 200 rows provided — request rejected
- date field does not match YYYY-MM-DD format — validation error
- field enum value not one of 'save_kb' or 'write_ms' — invalid input
- method enum not one of 'zero', 'mean', 'median' — invalid input
- All values for the selected field are null — mean/median imputation may be undefined
- numeric values outside allowed range (-1e12 to 1e12) — rejected

## How this service works

Save files — Daily sum series + Explicit missing-value fill: Daily sum series + 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 per call (for up to 200 input rows): a daily sum time series of the chosen metric (save_kb or write_ms), and the same series with missing values explicitly filled using the chosen 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/save-files-daily-sum-series-with-missing-value-fill-aa415b49/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)