{"uid":"cap_KUd0objJ4cHmmBGGbXkpn","slug":"compositing-graphs-string-normalisation-explicit-missing-value-fill-63468acd","name":"Compositing Graphs String Normalisation + Explicit Missing-Value Fill","description":"Compositing graphs — String normalisation + Explicit missing-value fill: String normalisation + 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-09-037?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_hNlHWIb4kdIzPqJCKY9kg","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":"Normalises strings and fills missing values for compositing graph records (node_count, render_seconds) across up to 200 rows, producing 2 analytical reports.","exampleAgentPrompt":"Can you clean up my compositing graph data by normalising the asset_group strings and filling in any missing node_count values using median imputation? I have 4 rows covering dates 2026-10-01 through 2026-10-04, with asset groups 'group-a' and 'group-b'.","exampleUseCases":[{"title":"Fill missing node counts in pipeline","prompt":"I have compositing graph records for October with some null node_count values — can you fill those missing values using median and give me the cleaned report? Here are 10 rows with row IDs row-1 through row-10, dates from 2026-10-01, and asset groups 'alpha' and 'beta'."},{"title":"Normalize render time data for reporting","prompt":"My render_seconds data for compositing jobs has some gaps and inconsistent string labels in asset_group — can you normalize the strings and fill missing render_seconds using mean imputation across my 50 compositing graph rows?"},{"title":"Zero-fill missing metrics for QA audit","prompt":"For a QA audit on our compositing pipeline, I need missing node_count values filled with zero and the strings normalized across 200 rows of compositing graph data with various asset groups and dates in 2026 — can you produce both reports?"}],"resultDescription":"Returns 2 analytical reports on the supplied compositing graph records: one covering string-normalised fields (asset_group) and one covering the chosen metric (node_count or render_seconds) with missing values explicitly filled using the selected method (zero, mean, or median). Up to 200 input rows are processed locally with no external lookups.","failureModes":["Input array is empty or exceeds 200 rows — validation error returned","Invalid date format (not YYYY-MM-DD) causes schema rejection","Missing required fields (row_id, asset_group, date) trigger validation failure","Invalid fill method or field enum value causes rejection","Extremely large numeric values near the boundary (±1e12) may cause computation edge cases"],"whenToPreferThis":"Choose this endpoint when you need lightweight, offline-style data cleaning for compositing graph records specifically — string normalisation of asset_group labels combined with structured missing-value imputation on node_count or render_seconds. It is ideal for small-to-medium batches (up to 200 rows) where you want a fixed-cost ($0.01 USDC) dual-report output without live lookups or external dependencies. Prefer alternatives if you need real-time data fetching, ML-based prediction, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T00:48:52.551Z","isFirstParty":false,"canonicalSlug":"compositing-graphs-string-normalisation-explicit-missing-value-fill-63468acd"}