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UI Screens Analytics — Secondary-Measure Weighted Mean + Explicit Missing-Value Fill
x402
UI Screens Analytics — Secondary-Measure Weighted Mean + 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 2026-10-24).
Computes a secondary-measure weighted mean and fills missing values for up to 200 UI screen records containing widget_count and render_ms fields, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
UI screens — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + Explicit missing-value fill for supplied ui screens records (widget_count, render_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 secondary-measure weighted mean result for the chosen field (widget_count or render_ms) using the other metric as weight, and (2) an explicit missing-value fill result applying the selected method (zero, mean, or median) across up to 200 supplied UI screen rows. No external lookups are performed; all computation uses local analytical engines.
Example use cases
Game UI render time analysis
“I've got 120 rows of UI screen data split across group-a and group-b game areas with render_ms and widget_count — some render_ms values are missing. Please compute the weighted mean for render_ms and fill the missing entries using mean imputation.”
Widget count missing-value fill for dashboards
“My UI screen dataset has 80 rows and several widget_count nulls. Can you fill those missing widget_count values using zero-fill and give me the secondary-measure weighted mean report?”
Cross-area screen performance comparison
“I have UI screen records for multiple game areas dated from 2026-10-01 through 2026-10-30 — about 150 rows total. Run the weighted mean on widget_count with median missing-value fill and return both analytical reports.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-16-187?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular UI screen records (with widget_count and render_ms) and need both a weighted mean aggregation and explicit missing-value imputation in a single call. Ideal for game UI performance analytics pipelines where you want two bundled statistical reports at low cost ($0.01 USDC) without external lookups or predictions. Prefer this over general-purpose analytics when your data fits the specific schema (row_id, game_area, date, widget_count, render_ms) and you need offline, deterministic statistical computation.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, game_area) on any row — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema validation failure
- Payment not received or insufficient USDC — x402 payment required response
- All values null for chosen field — weighted mean may be undefined or return NaN
- Invalid enum value for field or method parameters — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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