{"uid":"cap_nMZMLyMyDzNhwd8J-v94r","slug":"geospatial-tile-processing-record-quality-audit-missing-value-fill-e323e3a2","name":"Geospatial Tile Processing — Record Quality Audit + Missing-Value Fill","description":"Geospatial tile processing — Record quality audit + Explicit missing-value fill: Record quality audit + Explicit missing-value fill for supplied geospatial tile processing records (tile_count, processing_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-weather-21-019?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","tile_count","processing_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"tile_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80},"processing_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","tile_count":10,"station_group":"group-a","processing_seconds":1},{"date":"2026-10-02","row_id":"row-2","tile_count":20,"station_group":"group-b","processing_seconds":2},{"date":"2026-10-03","row_id":"row-3","tile_count":15,"station_group":"group-a","processing_seconds":3},{"date":"2026-10-04","row_id":"row-4","tile_count":30,"station_group":"group-b","processing_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["tile_count","processing_seconds"],"type":"string","default":"tile_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_fjLuZTaFcEvKhJvlscMTm","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":"Audits record quality and fills missing values (zero, mean, or median) for geospatial tile processing data (tile_count, processing_seconds) across up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit and fill any missing tile_count values using median imputation on my geospatial tile processing dataset — I have about 150 rows with fields like station_group, date, tile_count, and processing_seconds?","exampleUseCases":[{"title":"Audit tile pipeline for data gaps","prompt":"I've got a CSV of geospatial tile processing jobs — around 120 rows with station_group, date, tile_count, and processing_seconds — can you audit them for quality issues and flag any missing or suspicious records?"},{"title":"Impute missing processing times with mean","prompt":"Some of my tile processing records have null processing_seconds values. Can you fill those in using mean imputation across my 80-row dataset and give me the cleaned output?"},{"title":"Pre-ingestion data quality check for tile counts","prompt":"Before I load my tile processing data into the warehouse, can you do a quality audit and fill any missing tile_count values with zero for these 200 rows grouped by station_group?"}],"resultDescription":"Returns two independent reports: (1) a record quality audit identifying completeness issues, anomalies, or invalid entries per row; and (2) an explicit missing-value fill report showing the imputed values for the specified field (tile_count or processing_seconds) using the chosen method (zero, mean, or median). No external lookups or predictions are made — all analysis is local.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, tile_count, processing_seconds) causes row-level rejection","Invalid date format (non-YYYY-MM-DD) triggers a schema validation error","Invalid enum values for 'method' or 'field' parameters cause request rejection","Empty rows array returns an error","Numeric values outside ±1,000,000,000,000 may be rejected"],"whenToPreferThis":"Choose this endpoint when you need both a data quality audit and missing-value imputation for geospatial tile processing records in a single low-cost call. It is well-suited for pre-ingestion data cleaning pipelines where tile_count and processing_seconds are the key metrics, and when you need up to 200 rows processed with no external dependencies. It is not suitable for real-time tile rendering, geospatial coordinate lookups, or datasets requiring live external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:33:44.557Z","isFirstParty":false,"canonicalSlug":"geospatial-tile-processing-record-quality-audit-missing-value-fill-e323e3a2"}