{"uid":"cap_qpUk8s0Sfc6WIRNLK6SrA","slug":"dataset-partition-sizes-iqr-outlier-flags-missing-value-fill-abd00af8","name":"Dataset Partition Sizes — IQR Outlier Flags + Missing-Value Fill","description":"Dataset partition sizes — IQR outlier flags + Explicit missing-value fill: IQR outlier flags + Explicit missing-value fill for supplied dataset partition sizes records (row_count, file_mb). 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-07-180?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","row_count","file_mb"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"file_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","file_mb":1,"row_count":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","file_mb":2,"row_count":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","file_mb":3,"row_count":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","file_mb":4,"row_count":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["row_count","file_mb"],"type":"string","default":"row_count"},"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_b-Asr8PuZvgJBUlyYLNSL","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":"Analyzes dataset partition size records (row_count, file_mb) to flag IQR-based outliers and fill missing values using a chosen imputation method, returning two independent analytical reports.","exampleAgentPrompt":"Can you analyze these dataset partition records for outliers and fill in any missing row_count values using median imputation? I have up to 50 rows with fields like row_id, dataset_group, date, row_count, and file_mb.","exampleUseCases":[{"title":"ETL pipeline data quality check","prompt":"I've got 80 partition size records from our ETL pipeline — each has a row_id, dataset_group, date, row_count, and file_mb. Can you flag any IQR outliers in row_count and fill any missing row_count values using median?"},{"title":"File size anomaly detection for storage audit","prompt":"Run an IQR outlier analysis on file_mb across these 120 dataset partition records and fill any null file_mb values with the mean — I need to spot which partitions are abnormally large or small."},{"title":"Missing data imputation before ML feature engineering","prompt":"Before I feed these partition size records into my model, can you fill all missing row_count entries using zero and also flag any outlier row_counts based on IQR? I have about 150 rows with row_id, date, dataset_group, row_count, and file_mb."}],"resultDescription":"Returns two independent analytical reports: (1) IQR-based outlier flags identifying which records have row_count or file_mb values beyond the interquartile range boundaries, and (2) a missing-value fill report showing which records had nulls and what values were imputed using the chosen method (zero, mean, or median). All analysis is performed locally with no external lookups.","failureModes":["Input array exceeds 200 rows — request will be rejected","Invalid date format (must be YYYY-MM-DD) causes validation error","Missing required fields (row_id, dataset_group, date) cause schema validation failure","Numeric values outside allowed range trigger validation errors","Empty rows array rejected by minItems:1 constraint","Invalid method or field enum value causes request failure"],"whenToPreferThis":"Choose this endpoint when you have up to 200 dataset partition size records and need both IQR outlier detection and missing-value imputation in a single low-cost call. Ideal for data quality pipelines, pre-processing steps before ML or analytics, and storage audits where you need statistical anomaly flagging without external dependencies or live data lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:46.367Z","isFirstParty":false,"canonicalSlug":"dataset-partition-sizes-iqr-outlier-flags-missing-value-fill-abd00af8"}