{"uid":"cap_4yW2S6N4ommpBmkGe1b6C","slug":"dataset-storage-daily-sum-series-and-iqr-outlier-flags-analytics-bba46b56","name":"Dataset Storage Daily Sum Series and IQR Outlier Flags Analytics","description":"Dataset storage — Daily sum series + IQR outlier flags: Daily sum series + IQR outlier flags 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-18-140?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"}}},"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_lT1dnxeNMtt7PMuA8x3rT","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 daily sum time series and IQR-based outlier flags for dataset storage metrics (used_mb or row_count) from up to 200 supplied records","exampleAgentPrompt":"Take these dataset storage records and give me the daily sum series for used_mb plus flag any IQR outliers — I have about 50 rows across two groups, 'warehouse' and 'archive', spanning last month.","exampleUseCases":[{"title":"Detect storage spikes in ETL pipeline","prompt":"I have 120 rows of daily storage logs from our ETL pipeline with used_mb readings across three dataset groups — can you compute the daily total used_mb per day and flag which days are IQR outliers?"},{"title":"Monitor row count anomalies across groups","prompt":"Here are 80 records of dataset storage tracking row_count for groups 'prod' and 'staging' over the past quarter — give me the daily sum series for row_count and highlight any outlier days using IQR."},{"title":"Audit historical dataset growth trends","prompt":"I'm auditing our data warehouse and need a daily aggregated view of used_mb across all my dataset groups for the past 6 months — 200 rows total — plus IQR outlier flags so I can spot unusual growth days."}],"resultDescription":"Two analytical reports: (1) a daily sum time series showing the total of the selected metric (used_mb or row_count) aggregated per date, and (2) IQR-based outlier flags identifying which records or days fall outside the interquartile range bounds — all computed locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows submitted — exceeds limit, request rejected","Invalid date format not matching YYYY-MM-DD pattern — validation error","Missing required fields (row_id, dataset_group, date, used_mb, row_count) — schema error","All values null for the selected field — IQR computation may be undefined","Invalid field enum value (not 'used_mb' or 'row_count') — rejected","Payment not included or insufficient — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have raw dataset storage records (up to 200 rows) with used_mb or row_count fields and need both a daily aggregated time series AND statistical outlier detection in a single low-cost call. Prefer this over general analytics APIs when you want IQR-specific outlier flagging on storage metrics without sending data to a heavyweight analytics platform. Ideal for lightweight, offline-style analysis where you supply the data and get back structured reports instantly.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:47.264Z","isFirstParty":false,"canonicalSlug":"dataset-storage-daily-sum-series-and-iqr-outlier-flags-analytics-bba46b56"}