{"uid":"cap_ccZprv_bwCVn6Wffe8enH","slug":"ui-screens-analytics-secondary-measure-weighted-mean-explicit-missing-87025666","name":"UI Screens Analytics — Secondary-Measure Weighted Mean + Explicit Missing-Value Fill","description":"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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-game-16-187?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","game_area","date","widget_count","render_ms"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"game_area":{"type":"string","default":"","maxLength":80},"render_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"widget_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","game_area":"group-a","render_ms":1,"widget_count":10},{"date":"2026-10-02","row_id":"row-2","game_area":"group-b","render_ms":2,"widget_count":20},{"date":"2026-10-03","row_id":"row-3","game_area":"group-a","render_ms":3,"widget_count":15},{"date":"2026-10-04","row_id":"row-4","game_area":"group-b","render_ms":4,"widget_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["widget_count","render_ms"],"type":"string","default":"widget_count"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_mJKrpMNQ1LBW50-m1s6Vx","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"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.","exampleAgentPrompt":"I have UI screen records for two game areas with widget_count and render_ms values — some entries have nulls. Can you compute the secondary-measure weighted mean for render_ms and fill the missing values using median imputation across my 50 rows?","exampleUseCases":[{"title":"Game UI render time analysis","prompt":"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."},{"title":"Widget count missing-value fill for dashboards","prompt":"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?"},{"title":"Cross-area screen performance comparison","prompt":"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."}],"resultDescription":"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.","failureModes":["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"],"whenToPreferThis":"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.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:52:27.020Z","isFirstParty":false,"canonicalSlug":"ui-screens-analytics-secondary-measure-weighted-mean-explicit-missing-87025666"}