{"uid":"cap_cAthf6C_HW28ZQwZ213tx","slug":"data-catalog-coverage-string-normalisation-explicit-missing-value-fill-2762ac22","name":"Data Catalog Coverage — String Normalisation + Explicit Missing-Value Fill","description":"Data catalog coverage — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied data catalog coverage records (documented_fields, total_fields). 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-21-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","documented_fields","total_fields"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_fields":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"documented_fields":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_fields":1,"dataset_group":"group-a","documented_fields":10},{"date":"2026-10-02","row_id":"row-2","total_fields":2,"dataset_group":"group-b","documented_fields":20},{"date":"2026-10-03","row_id":"row-3","total_fields":3,"dataset_group":"group-a","documented_fields":15},{"date":"2026-10-04","row_id":"row-4","total_fields":4,"dataset_group":"group-b","documented_fields":30}],"maxItems":200,"minItems":1},"field":{"enum":["documented_fields","total_fields"],"type":"string","default":"documented_fields"},"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_LYhgc77Tc8kc2abQeI-OI","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":"Normalises strings and fills missing values in data catalog coverage records (documented_fields, total_fields) for up to 200 rows, producing 2 analytical reports.","exampleAgentPrompt":"Can you clean up my data catalog coverage records — normalise the strings and fill any missing documented_fields values using median imputation? I have 4 rows with dataset_group, date, documented_fields, and total_fields columns.","exampleUseCases":[{"title":"Imputing missing field counts for governance audit","prompt":"I have a data catalog coverage table with some null documented_fields entries — can you fill those missing values using the mean and also normalise the string columns? Here are my rows: row-1 group-a 2026-10-01 documented_fields=null total_fields=50, row-2 group-b 2026-10-02 documented_fields=30 total_fields=60."},{"title":"Standardising dataset group labels before reporting","prompt":"Before I generate our quarterly catalog coverage report, can you normalise the string formatting in my dataset_group names and fill any missing total_fields values with zero? I'll send you 10 rows covering October."},{"title":"Cleaning coverage data for a data quality dashboard","prompt":"I need to prep my data catalog coverage records for our quality dashboard — please normalise strings and fill null documented_fields using median for these 5 rows: row-1 through row-5, dates 2026-10-01 to 2026-10-05, groups alpha and beta."}],"resultDescription":"Two analytical reports per call: one covering string normalisation results and one covering explicit missing-value fill results for up to 200 supplied data catalog coverage rows (documented_fields or total_fields), all computed locally with no external lookups.","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, date, dataset_group) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Invalid fill method value outside enum (zero/mean/median) — error","Invalid field value outside allowed enum (documented_fields/total_fields) — error","Numeric values outside allowed range — schema rejection"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local string normalisation and missing-value imputation specifically for data catalog coverage records (documented_fields/total_fields) in batches up to 200 rows, and you want two bundled reports for a flat $0.01 USDC fee without any external API calls or live data lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:52:01.209Z","isFirstParty":false,"canonicalSlug":"data-catalog-coverage-string-normalisation-explicit-missing-value-fill-2762ac22"}