{"uid":"cap_32DsvwgTdwVhZ3X3nPhdz","slug":"dataset-storage-analytics-two-measure-correlation-missing-value-fill-58888c7f","name":"Dataset Storage Analytics — Two-Measure Correlation + Missing-Value Fill","description":"Dataset storage — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied dataset storage records (used_mb, row_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-analytics-18-184?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","used_mb","row_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"used_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","used_mb":10,"row_count":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","used_mb":20,"row_count":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","used_mb":15,"row_count":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","used_mb":30,"row_count":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["used_mb","row_count"],"type":"string","default":"used_mb"},"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_K80vG3m5Aal4dq8wxmhj-","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":"Computes Pearson correlation between used_mb and row_count, and fills missing values using a chosen strategy (zero, mean, or median), for up to 200 dataset storage records.","exampleAgentPrompt":"Can you analyze my dataset storage records — I have up to 50 rows with used_mb and row_count fields — and compute the correlation between those two measures while also filling any missing used_mb values using the median strategy?","exampleUseCases":[{"title":"Storage growth correlation analysis","prompt":"I have 120 rows of dataset storage logs with used_mb and row_count per group and date. Can you compute the Pearson correlation between used_mb and row_count to see if larger datasets actually consume more storage?"},{"title":"Missing storage metrics imputation","prompt":"Some of my dataset records are missing row_count values. Can you fill those in using the mean of the existing row_count values across my 80 storage rows so the dataset is complete for downstream analysis?"},{"title":"Pre-pipeline data quality for ETL","prompt":"Before I run my ETL pipeline I need to validate and clean my dataset storage table — about 150 rows with used_mb and row_count. Fill any nulls in used_mb using zero and tell me the correlation between the two measures."}],"resultDescription":"Returns two analytical reports: (1) a correlation result showing the statistical relationship (Pearson r) between used_mb and row_count across the submitted rows, and (2) the dataset with missing values in the specified field filled using the chosen strategy (zero, mean, or median). Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Invalid date format (not YYYY-MM-DD) causes schema rejection","Missing required fields (row_id, dataset_group, date) cause row-level errors","Fewer than 2 non-null values may produce undefined or NaN correlation","Invalid enum for method or field causes a 400-level error","Payment not attached or insufficient USDC causes x402 payment-required response"],"whenToPreferThis":"Choose this endpoint when you need to simultaneously assess the linear relationship between two storage metrics (used_mb and row_count) and clean missing values in a single API call, for small-to-medium datasets up to 200 rows. It is cost-effective at $0.01 USDC for both reports together. Prefer it over generic statistical libraries when you need a hosted, stateless, pay-per-call analytical service that requires no infrastructure setup.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:11.459Z","isFirstParty":false,"canonicalSlug":"dataset-storage-analytics-two-measure-correlation-missing-value-fill-58888c7f"}