{"uid":"cap_f1RaGl5NutiuzL0Tnx-Gg","slug":"geospatial-tile-processing-exact-row-deduplication-date-by-category-77f4ec03","name":"Geospatial Tile Processing — Exact Row Deduplication + Date by Category Pivot","description":"Geospatial tile processing — Exact row deduplication + Date by category pivot: Exact row deduplication + Date by category pivot 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-21-052?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"}}},"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_MeM8FxoAOO19GuSN82bXg","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":"Deduplicates geospatial tile processing records and pivots date values by category (station_group), returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have a batch of geospatial tile processing records with tile_count and processing_seconds — can you deduplicate the exact duplicate rows and also pivot the dates by station group? Here are my rows: row-1 (group-a, 2026-10-01, tile_count=10, processing_seconds=1), row-2 (group-b, 2026-10-02, tile_count=20, processing_seconds=2), row-3 (group-a, 2026-10-03, tile_count=15, processing_seconds=3). Run the analysis on the tile_count field.","exampleUseCases":[{"title":"Deduplicating pipeline tile logs","prompt":"I've got up to 150 rows of geospatial tile processing logs and I suspect there are exact duplicates — can you deduplicate them and also pivot the dates by station group so I can see how tile_count breaks down across groups and dates?"},{"title":"Cross-tabulating processing seconds by group","prompt":"Take these 80 tile processing records with station groups and dates and give me both an exact deduplication report and a date-by-category pivot focused on processing_seconds across the station groups."},{"title":"Auditing tile counts across station groups","prompt":"I need to audit my tile processing dataset for duplicate entries and also see a pivot of tile_count values by date and station_group — I have about 200 rows ready to submit."}],"resultDescription":"Returns two analytical reports: (1) an exact row deduplication report identifying and removing fully duplicated rows from the submitted geospatial tile processing records, and (2) a date-by-category pivot table showing the selected metric (tile_count or processing_seconds) cross-tabulated by date and station_group. Both reports are computed locally from the submitted data with no external lookups.","failureModes":["Exceeds 200-row limit — request rejected or truncated","Invalid date format not matching YYYY-MM-DD pattern — validation error","Missing required fields (row_id, station_group, date, tile_count, or processing_seconds) — schema validation failure","Numeric values outside allowed range — rejection","Empty rows array — schema validation failure","Invalid field enum value (not tile_count or processing_seconds) — error"],"whenToPreferThis":"Choose this endpoint when you have geospatial tile processing records (with tile_count and processing_seconds) and need both exact deduplication and a date-by-category pivot in a single low-cost call. It is best for datasets up to 200 rows where no live data lookup, external enrichment, or predictive modeling is needed — purely local analytical computation on supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T06:41:45.972Z","isFirstParty":false,"canonicalSlug":"geospatial-tile-processing-exact-row-deduplication-date-by-category-77f4ec03"}