{"uid":"cap_KjlAbj2Z1GK7uKAFW4bdH","slug":"geospatial-tile-processing-numeric-row-ordering-explicit-missing-82c0fadb","name":"Geospatial Tile Processing — Numeric Row Ordering + Explicit Missing-Value Fill","description":"Geospatial tile processing — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + 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-21-124?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_bOwZvkv9QOafhRLlKYIu0","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":"Sorts geospatial tile processing records by a numeric field and fills in missing values using zero, mean, or median strategies for up to 200 rows.","exampleAgentPrompt":"I have a dataset of geospatial tile processing records with some missing tile_count values — can you sort the rows numerically by tile_count and fill in the missing ones using the median, for these 4 rows: row-1 on 2026-10-01 in group-a with tile_count 10 and processing_seconds 1, row-2 on 2026-10-02 in group-b with tile_count null and processing_seconds 2, row-3 on 2026-10-03 in group-a with tile_count 15 and processing_seconds 3, row-4 on 2026-10-04 in group-b with tile_count 30 and processing_seconds 4?","exampleUseCases":[{"title":"Impute missing tile counts for QA pipeline","prompt":"I have 50 geospatial tile processing records where some tile_count values are null — sort them numerically by tile_count and fill the missing ones with the mean so our QA pipeline gets a clean dataset."},{"title":"Order processing time records for reporting","prompt":"Can you take my 80 tile processing rows and sort them by processing_seconds in numeric order, filling any missing processing_seconds values with zero? I need a clean ordered report for the operations team."},{"title":"Clean station group tile data before analysis","prompt":"I need to clean up my geospatial tile dataset from group-a and group-b stations — sort the 120 records by tile_count numerically and use median imputation for any missing tile_count values so I can feed it into our analysis."}],"resultDescription":"Returns two analytical reports on the submitted geospatial tile processing records: one showing rows ordered numerically by the selected field (tile_count or processing_seconds), and one showing rows with missing values in that field explicitly filled using the chosen strategy (zero, mean, or median). Covers up to 200 input rows.","failureModes":["Input exceeds 200 rows — request will be rejected","Invalid date format not matching YYYY-MM-DD pattern — validation error","Missing required fields (row_id, station_group, date) — schema validation failure","Field values outside allowed numeric range (±1,000,000,000,000) — rejected","Invalid method enum value (not zero/mean/median) — rejected","Invalid field enum (not tile_count/processing_seconds) — rejected","Payment not processed — endpoint returns 402"],"whenToPreferThis":"Choose this endpoint when you have a structured dataset of geospatial tile processing records (with tile_count and/or processing_seconds columns) and need both numeric row ordering and explicit missing-value imputation in a single call, without any live data lookup, prediction, or external action. It is ideal for data cleaning and preprocessing pipelines where datasets have up to 200 rows and you want reproducible, locally computed analytical reports at low cost ($0.01 USDC for 2 reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:33:54.953Z","isFirstParty":false,"canonicalSlug":"geospatial-tile-processing-numeric-row-ordering-explicit-missing-82c0fadb"}