{"uid":"cap_0NgWEDUUcbdP9YdnICFIX","slug":"compositing-graphs-iqr-outlier-flags-missing-value-fill-befe45ae","name":"Compositing Graphs IQR Outlier Flags + Missing-Value Fill","description":"Compositing graphs — IQR outlier flags + Explicit missing-value fill: IQR outlier flags + Explicit missing-value fill for supplied compositing graphs records (node_count, render_seconds). 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-creative-09-180?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","node_count","render_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"node_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"asset_group":{"type":"string","default":"","maxLength":80},"render_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","node_count":10,"asset_group":"group-a","render_seconds":1},{"date":"2026-10-02","row_id":"row-2","node_count":20,"asset_group":"group-b","render_seconds":2},{"date":"2026-10-03","row_id":"row-3","node_count":15,"asset_group":"group-a","render_seconds":3},{"date":"2026-10-04","row_id":"row-4","node_count":30,"asset_group":"group-b","render_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["node_count","render_seconds"],"type":"string","default":"node_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_O2tZ1VI0JPdhuQc1Uewen","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":"Runs IQR-based outlier detection and explicit missing-value imputation on compositing graph records (node_count, render_seconds) — up to 200 rows, two reports per call.","exampleAgentPrompt":"Can you flag IQR outliers and fill missing values in my compositing graph data using median imputation? I have about 50 rows with node_count and render_seconds fields — here's the dataset.","exampleUseCases":[{"title":"QA on rendering pipeline metrics","prompt":"I've got 120 rows of compositing graph data with node_count and render_seconds per asset group and date — can you flag any IQR outliers in node_count and fill missing node_count values using the mean?"},{"title":"Clean render time data before reporting","prompt":"Before I generate our weekly render report, can you run outlier detection and median-based missing-value fill on my render_seconds compositing graph records? I'll send you up to 80 rows."},{"title":"Detect anomalous node counts by asset group","prompt":"Something looks off in our compositing graph stats — can you use IQR outlier flagging on the node_count field and fill any gaps with zero for these 200 rows grouped by asset_group?"}],"resultDescription":"Returns two independent analytical reports per call: (1) IQR outlier flags identifying which rows have statistically anomalous values for the selected field, and (2) a missing-value fill report showing which null/missing entries were imputed and with what value (zero, mean, or median). Results are computed locally without external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, asset_group) cause schema rejection","Invalid date format (non-YYYY-MM-DD) triggers pattern validation failure","Numeric values outside ±1,000,000,000,000 range are rejected","Empty rows array returns an error","Invalid enum for method or field causes request rejection"],"whenToPreferThis":"Choose this endpoint when you need both IQR outlier flagging AND missing-value imputation on compositing graph data (node_count or render_seconds) in a single low-cost call. It is ideal for data quality checks on rendering pipeline metrics before downstream analysis or reporting, and is purpose-built for the compositing graph schema with asset_group and date dimensions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T12:43:10.741Z","isFirstParty":false,"canonicalSlug":"compositing-graphs-iqr-outlier-flags-missing-value-fill-befe45ae"}