{"uid":"cap_eu8oYsIzugOonuBAwva0Y","slug":"coordinate-quality-checks-grouped-numeric-summary-explicit-missing-f7308552","name":"Coordinate Quality Checks — Grouped Numeric Summary + Explicit Missing-Value Fill","description":"Coordinate quality checks — Grouped numeric summary + Explicit missing-value fill: Grouped numeric summary + Explicit missing-value fill for supplied coordinate quality checks records (checked_points, flagged_points). 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-23-099?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","checked_points","flagged_points"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"station_group":{"type":"string","default":"","maxLength":80},"checked_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"flagged_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","station_group":"group-a","checked_points":10,"flagged_points":1},{"date":"2026-10-02","row_id":"row-2","station_group":"group-b","checked_points":20,"flagged_points":2},{"date":"2026-10-03","row_id":"row-3","station_group":"group-a","checked_points":15,"flagged_points":3},{"date":"2026-10-04","row_id":"row-4","station_group":"group-b","checked_points":30,"flagged_points":4}],"maxItems":200,"minItems":1},"field":{"enum":["checked_points","flagged_points"],"type":"string","default":"checked_points"},"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_gqMivTfQfSOJz1Jclvt32","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 grouped numeric summaries and fills missing values (zero, mean, or median) for coordinate quality check records containing checked_points and flagged_points fields.","exampleAgentPrompt":"I have up to 200 rows of coordinate quality check records with station_group, date, checked_points, and flagged_points — can you run a grouped numeric summary and fill any missing checked_points values using median imputation?","exampleUseCases":[{"title":"Station group quality audit","prompt":"I have 150 rows of daily coordinate quality checks across station groups A, B, and C with checked_points and flagged_points. Can you group them by station and give me a numeric summary, and fill any missing checked_points values using the median?"},{"title":"Missing flagged_points imputation","prompt":"My quality check dataset has some null flagged_points entries. Can you fill those missing values using zero-fill and also produce a grouped summary report broken down by station_group and date?"},{"title":"Multi-group flagged ratio analysis","prompt":"I've got 80 rows of coordinate QC records with checked_points and flagged_points across several station groups — run a grouped numeric summary on flagged_points and use mean imputation to fill any gaps so I can compare flag rates across groups."}],"resultDescription":"Returns two analytical reports: (1) a grouped numeric summary aggregating checked_points and flagged_points by station_group, and (2) a report showing explicit missing-value fills applied to the selected field using the chosen method (zero, mean, or median). Covers up to 200 input rows with no external data lookups.","failureModes":["Input array exceeds 200 rows — request will be rejected or truncated","Missing required fields (row_id, station_group, date, checked_points, flagged_points) cause row-level errors","Invalid date format (not YYYY-MM-DD) causes parsing failure","Numeric values outside the allowed range (-1e12 to 1e12) may be rejected","Empty rows array returns no analytical output","Invalid method or field enum values cause validation errors"],"whenToPreferThis":"Choose this endpoint when you have tabular coordinate quality check data (checked_points, flagged_points) organized by station group and date, and need both a grouped statistical summary and missing-value imputation in a single call. It is purpose-built for offline batch analytics on up to 200 rows without needing external lookups, live data, or prediction services.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:10:39.947Z","isFirstParty":false,"canonicalSlug":"coordinate-quality-checks-grouped-numeric-summary-explicit-missing-f7308552"}