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Save Files Analytics — Two-Measure Correlation + Explicit Missing-Value Fill
x402
Save Files Analytics — Two-Measure Correlation + 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).
Computes Pearson/rank correlation between save_kb and write_ms fields and fills missing values using zero, mean, or median strategy for up to 200 game save-file records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Save files — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + 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 independent analytical reports: (1) a two-measure correlation report showing the statistical relationship (e.g. Pearson or Spearman coefficient) between save_kb and write_ms across submitted rows, and (2) an explicit missing-value fill report showing which rows had null values and what replacement values were applied using the chosen strategy (zero, mean, or median). No external data is fetched; all computation is local.
Example use cases
Game save performance correlation study
“I've got 150 rows of game save records with fields like row_id, game_area, date, save_kb, and write_ms — please compute the correlation between save file size and write latency, and fill any missing save_kb values using the mean.”
Missing write latency imputation for game data
“My game save dataset has some null write_ms values — can you fill those missing entries using the median and also give me the correlation between save_kb and write_ms across all 80 rows?”
Cross-area save file analytics
“I have save file data for two game areas, group-a and group-b, across October 2026 — run a two-measure correlation on save_kb and write_ms and fill any missing write_ms values with zero for my 40 rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-13-184?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have game save-file performance data (save file sizes and write latencies) and need both a correlation analysis and missing-value imputation in a single call at very low cost ($0.01). It is ideal for offline/batch analytical jobs on up to 200 rows where no live data lookup or prediction is needed. Prefer this over general-purpose analytics APIs when your data specifically involves save_kb and write_ms metrics segmented by game_area.
Side effects
- Fewer than 1 row submitted — minimum row count not met
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, game_area, date, save_kb, or write_ms) in one or more rows
- Date field does not match YYYY-MM-DD pattern — validation error
- Invalid fill method enum value (must be zero, mean, or median)
- Invalid field enum value (must be save_kb or write_ms)
- Numeric values outside allowed range (±1,000,000,000,000)
- Payment of 0.01 USDC not provided or declined — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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