{"uid":"cap_b_UUDLhfHhvrofIvVuL2U","slug":"image-exports-adjacent-row-changes-and-explicit-missing-value-fill-50d9ab51","name":"Image Exports Adjacent Row Changes and Explicit Missing-Value Fill","description":"Image exports — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied image exports records (width_pixels, height_pixels). 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-17-162?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","width_pixels","height_pixels"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"asset_group":{"type":"string","default":"","maxLength":80},"width_pixels":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"height_pixels":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","asset_group":"group-a","width_pixels":10,"height_pixels":1},{"date":"2026-10-02","row_id":"row-2","asset_group":"group-b","width_pixels":20,"height_pixels":2},{"date":"2026-10-03","row_id":"row-3","asset_group":"group-a","width_pixels":15,"height_pixels":3},{"date":"2026-10-04","row_id":"row-4","asset_group":"group-b","width_pixels":30,"height_pixels":4}],"maxItems":200,"minItems":1},"field":{"enum":["width_pixels","height_pixels"],"type":"string","default":"width_pixels"},"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_XVAG4UMTDo-ay5QZReD_J","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 adjacent row changes and fills missing values (zero/mean/median) in image export records containing width_pixels and height_pixels fields, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have a set of image export records with dates, asset groups, and pixel dimensions — can you run adjacent row change detection and fill any missing width_pixels values using the median method on these rows?","exampleUseCases":[{"title":"Audit image dimension consistency over time","prompt":"I have 50 daily image export records across two asset groups with some missing width_pixels values — please fill the nulls using median and show me how the width changed between each consecutive row."},{"title":"Detect sudden size spikes in export pipeline","prompt":"Can you analyze these image export logs and flag where the height_pixels jumped significantly between adjacent rows? Fill any missing height_pixels using the mean before running the analysis."},{"title":"Clean and diff export records before reporting","prompt":"I'm preparing a report on image exports for groups A and B from last month — fill missing width_pixels with zero and show me the row-to-row changes so I can spot anomalies before I hand this off."}],"resultDescription":"Returns two reports: (1) an adjacent row change report showing the delta in the chosen pixel dimension (width_pixels or height_pixels) between consecutive rows, and (2) a missing-value fill report showing which rows had null values and what fill value was substituted using the selected method (zero, mean, or median). Both reports cover the same up to 200 supplied rows and are produced by local analytical engines with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Both width_pixels and height_pixels are null for most rows, degrading mean/median fill quality","Unknown field value outside enum causes validation error","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you have image export records with width_pixels and height_pixels and need both row-to-row change detection and missing-value imputation in a single $0.01 call. It is especially useful for data-quality pipelines where pixel dimension nulls must be filled before downstream analysis. Prefer it over generic stats endpoints when your data is specifically image export records with the asset_group and date structure expected here.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:36:52.484Z","isFirstParty":false,"canonicalSlug":"image-exports-adjacent-row-changes-and-explicit-missing-value-fill-50d9ab51"}