{"uid":"cap_fGeeEcG_RXWoYb6r3mpGy","slug":"dataset-partition-sizes-base-100-series-iqr-outlier-flags-60fe4607","name":"Dataset Partition Sizes — Base-100 Series + IQR Outlier Flags","description":"Dataset partition sizes — Base-100 series + IQR outlier flags: Base-100 series + IQR outlier flags 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-07-164?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_hhyybSbqAouK3jqYNMBwT","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 a Base-100 indexed time series and IQR-based outlier flags for dataset partition size metrics (row_count or file_mb) across up to 200 supplied records.","exampleAgentPrompt":"Can you run a base-100 series and IQR outlier analysis on my dataset partitions? I have 4 rows — group-a had 10 rows and 1 MB on 2026-10-01, group-b had 20 rows and 2 MB on 2026-10-02, group-a had 15 rows and 3 MB on 2026-10-03, and group-b had 30 rows and 4 MB on 2026-10-04 — use row_count as the field and start the base index at row 0.","exampleUseCases":[{"title":"Monitoring partition growth anomalies","prompt":"I have weekly snapshots of my data warehouse partitions — 50 rows with row_count and file_mb per partition group — can you normalize the file_mb values to a base-100 series starting at row 0 and flag any IQR outliers so I know which weeks had abnormal file sizes?"},{"title":"Detecting outlier shards in ETL pipeline","prompt":"After my ETL runs, I collect partition stats for each shard. Can you take my 120 records of row_count data across multiple dataset groups, compute a base-100 index from the first row, and tell me which partitions are flagged as IQR outliers?"},{"title":"Benchmarking dataset size trends over time","prompt":"I want to see how my dataset partition sizes have grown relative to a baseline — I have 80 rows of daily partition data with file_mb values across two groups. Can you build a base-100 series using row 5 as the base and also show me which records are outliers by IQR?"}],"resultDescription":"Returns two analytical reports for the supplied dataset partition records: (1) a Base-100 indexed series showing each row's metric value relative to the chosen base row, and (2) IQR-based outlier flags marking which records fall outside the interquartile range. Both reports are computed locally on the supplied data with no external lookups.","failureModes":["Fewer than 1 row submitted — validation error","More than 200 rows submitted — request rejected due to maxItems constraint","Invalid date format (not YYYY-MM-DD) — schema validation failure","base_index out of range (>= number of rows submitted) — computation error","null values in the selected field (row_count or file_mb) may affect IQR computation","Missing required row fields (row_id, dataset_group, date) — schema rejection"],"whenToPreferThis":"Choose this endpoint when you need both a relative-growth (Base-100) normalization and IQR-based outlier detection on dataset partition metrics in a single call, without any external data sources. It is purpose-built for partition size analytics (row_count and file_mb) on batches of up to 200 records and is ideal when you want two independent analytical reports bundled at low cost. Prefer alternatives if you need daily sum aggregation, histogram binning, or real-time external data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:44.261Z","isFirstParty":false,"canonicalSlug":"dataset-partition-sizes-base-100-series-iqr-outlier-flags-60fe4607"}