{"uid":"cap_ZeFtzOY7MD39QgUaDvrRZ","slug":"numeric-precision-comparisons-row-ordering-missing-value-fill-ef30367e","name":"Numeric Precision Comparisons — Row Ordering & Missing-Value Fill","description":"Numeric precision comparisons — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied numeric precision comparisons records (source_value, transformed_value). 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-analytics-20-124?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","source_value","transformed_value"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"transformed_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_value":10,"dataset_group":"group-a","transformed_value":1},{"date":"2026-10-02","row_id":"row-2","source_value":20,"dataset_group":"group-b","transformed_value":2},{"date":"2026-10-03","row_id":"row-3","source_value":15,"dataset_group":"group-a","transformed_value":3},{"date":"2026-10-04","row_id":"row-4","source_value":30,"dataset_group":"group-b","transformed_value":4}],"maxItems":200,"minItems":1},"field":{"enum":["source_value","transformed_value"],"type":"string","default":"source_value"},"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_ha7xs9koRATxXSVK_7woD","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 numeric rows and fills missing values (zero, mean, or median) for source_value/transformed_value pairs across up to 200 supplied records, producing 2 analytical reports.","exampleAgentPrompt":"I have 4 rows of source and transformed values — some nulls included — can you sort them numerically by source_value and fill any missing entries using median imputation? Rows: row-1 group-a 2026-10-01 source=10 transformed=null, row-2 group-b 2026-10-02 source=20 transformed=2, row-3 group-a 2026-10-03 source=null transformed=3, row-4 group-b 2026-10-04 source=30 transformed=4.","exampleUseCases":[{"title":"ETL pipeline null patching and sorting","prompt":"I'm running an ETL job and my dataset has some null source_values — can you fill the missing ones using the column median and then sort all 12 rows numerically? Here are the rows grouped by dataset_group with dates from 2026-10-01 onward."},{"title":"Financial data transformation QA","prompt":"I need to QA my financial transformation pipeline — take these 50 rows of source_value and transformed_value pairs (some nulls in transformed_value), fill missing transformed values with zero, and give me the rows sorted by transformed_value so I can spot anomalies."},{"title":"ML feature comparison pre-processing","prompt":"Before I train my model, I need to compare my raw and transformed feature columns across 80 rows — fill any nulls in source_value using the mean, sort everything by source_value ascending, and give me both reports so I can see if the transformation looks sane."}],"resultDescription":"Returns 2 analytical reports covering: (1) rows sorted in numeric order by the specified field, and (2) missing values in that field explicitly filled using the chosen method (zero, mean, or median). Output is scoped to the supplied data only — no external lookups or predictions.","failureModes":["More than 200 rows submitted — request rejected at maxItems limit","Invalid date format (not YYYY-MM-DD) — schema validation error","source_value or transformed_value outside allowed range (-1T to +1T) — validation failure","Unrecognized fill method or field enum value — schema rejection","Empty rows array (minItems=1 not met) — validation error","Payment not included or insufficient USDC — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of paired numeric values (source and transformed) and need both ordered ranking and explicit null imputation in a single call for $0.01 USDC. It is purpose-built for numeric precision comparison workflows — ideal for ETL QA, data transformation validation, or pre-processing checks — and delivers two bundled reports without any external data fetching or ML inference overhead.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:14.903Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-row-ordering-missing-value-fill-ef30367e"}