{"uid":"cap_W18zxkk9ay9TwEfD0-l5-","slug":"curriculum-mapping-string-normalisation-and-missing-value-fill-0b70ac2a","name":"Curriculum Mapping String Normalisation and Missing-Value Fill","description":"Curriculum mapping — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied curriculum mapping records (mapped_outcomes, required_outcomes). 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-education-24-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","course_group","date","mapped_outcomes","required_outcomes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"course_group":{"type":"string","default":"","maxLength":80},"mapped_outcomes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"required_outcomes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","course_group":"group-a","mapped_outcomes":10,"required_outcomes":1},{"date":"2026-10-02","row_id":"row-2","course_group":"group-b","mapped_outcomes":20,"required_outcomes":2},{"date":"2026-10-03","row_id":"row-3","course_group":"group-a","mapped_outcomes":15,"required_outcomes":3},{"date":"2026-10-04","row_id":"row-4","course_group":"group-b","mapped_outcomes":30,"required_outcomes":4}],"maxItems":200,"minItems":1},"field":{"enum":["mapped_outcomes","required_outcomes"],"type":"string","default":"mapped_outcomes"},"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_PI3G-CxNViiku92dhdV8e","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 curriculum mapping records (mapped_outcomes, required_outcomes) for up to 200 rows, producing 2 analytical reports.","exampleAgentPrompt":"Clean my curriculum mapping dataset — I have up to 50 rows with row_id, course_group, date, mapped_outcomes, and required_outcomes fields; fill any missing mapped_outcomes values using the median method and give me both the string normalisation and missing-value fill reports.","exampleUseCases":[{"title":"Filling missing outcomes for IB courses","prompt":"I have a batch of 80 IB curriculum mapping rows where some mapped_outcomes values are null — can you fill those missing values using the mean and also normalise the strings across all rows?"},{"title":"Zero-filling required outcomes in course audit","prompt":"I'm auditing our course records and need to replace any blank required_outcomes entries with zero, then get a normalisation report for all 120 rows in my curriculum dataset."},{"title":"Preparing clean curriculum data for reporting","prompt":"Before I send this curriculum mapping data to our accreditation team, can you normalise the strings and fill any missing mapped_outcomes using the median for these 200 course group rows?"}],"resultDescription":"Returns two analytical reports: (1) a string normalisation report covering all supplied curriculum mapping records, and (2) an explicit missing-value fill report for the specified field (mapped_outcomes or required_outcomes) using the chosen fill method (zero, mean, or median). No external lookups or predictions are made; all analysis uses local engines on the supplied data.","failureModes":["Rows array exceeds 200 items — request rejected","Missing required fields (row_id, date, mapped_outcomes, required_outcomes) in any row — validation error","Date field does not match YYYY-MM-DD pattern — schema validation failure","Invalid enum value for field or method parameter — bad request error","Empty rows array — minimum 1 item required"],"whenToPreferThis":"Choose this endpoint when you need lightweight, deterministic string normalisation and missing-value imputation on curriculum mapping records (mapped_outcomes, required_outcomes) without any live data lookup, prediction, or external action. It is ideal for pre-processing educational outcome data before reporting or analysis, particularly when you need two independent reports (normalisation + fill) in a single cheap call ($0.01 USDC) for batches of up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:51:07.907Z","isFirstParty":false,"canonicalSlug":"curriculum-mapping-string-normalisation-and-missing-value-fill-0b70ac2a"}