{"uid":"cap_rfeg598_iJNh8V8TkgZYg","slug":"tutoring-sessions-iqr-outlier-flags-missing-value-fill-3c74da15","name":"Tutoring Sessions IQR Outlier Flags + Missing Value Fill","description":"Tutoring sessions — IQR outlier flags + Explicit missing-value fill: IQR outlier flags + Explicit missing-value fill for supplied tutoring sessions records (session_minutes, session_count). 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-16-180?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","course_group","date","session_minutes","session_count"],"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},"session_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"session_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","course_group":"group-a","session_count":1,"session_minutes":10},{"date":"2026-10-02","row_id":"row-2","course_group":"group-b","session_count":2,"session_minutes":20},{"date":"2026-10-03","row_id":"row-3","course_group":"group-a","session_count":3,"session_minutes":15},{"date":"2026-10-04","row_id":"row-4","course_group":"group-b","session_count":4,"session_minutes":30}],"maxItems":200,"minItems":1},"field":{"enum":["session_minutes","session_count"],"type":"string","default":"session_minutes"},"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_05Q3-_AtCsESlY72YpSM7","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":"Detects IQR-based outliers and fills missing values in tutoring session data (session_minutes, session_count) for up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"Can you run IQR outlier detection and fill any missing session_minutes values using median imputation on my tutoring session records? I have up to 50 rows with row_id, course_group, date, session_minutes, and session_count fields.","exampleUseCases":[{"title":"Flag anomalous tutoring durations by group","prompt":"I have 80 rows of tutoring session logs with course_group, date, and session_minutes. Can you flag any session_minutes values that are IQR outliers and fill any missing ones using the median?"},{"title":"Impute missing session counts with mean","prompt":"Some rows in my tutoring dataset are missing session_count values. Can you run a missing-value fill using the mean method on the session_count field across my 120 tutoring records, and also flag any outliers?"},{"title":"Data quality check before reporting","prompt":"Before I submit my weekly education report, can you check my 200 tutoring session rows for IQR-based outliers in session_minutes and fill any nulls with zero so I have a clean dataset?"}],"resultDescription":"Returns two analytical reports per call: (1) IQR outlier flags per row indicating which session_minutes or session_count values fall outside the interquartile range, and (2) explicit missing-value fills for null entries using the selected method (zero, mean, or median). Results cover up to 200 input rows and are computed locally without external lookups.","failureModes":["Exceeding 200 rows returns an error or truncation","Invalid date format (not YYYY-MM-DD) causes row rejection","Missing required fields (row_id, course_group, date) causes validation failure","Numeric values outside bounds (±1,000,000,000,000) may be rejected","Empty rows array returns an error","Invalid enum value for method or field causes schema validation failure"],"whenToPreferThis":"Choose this endpoint when you need lightweight, deterministic statistical data quality analysis on tutoring session records — specifically IQR outlier detection combined with missing value imputation — without requiring external data sources, ML models, or live lookups. Ideal for pre-processing education datasets before reporting or dashboarding, especially when working with up to 200 rows and needing both reports in a single low-cost API call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T12:42:47.932Z","isFirstParty":false,"canonicalSlug":"tutoring-sessions-iqr-outlier-flags-missing-value-fill-3c74da15"}