{"uid":"cap_1NzPtnIUTn-n9K7SV_9BR","slug":"numeric-precision-comparisons-iqr-outlier-flags-date-by-category-pivot-9e16a06e","name":"Numeric Precision Comparisons — IQR Outlier Flags + Date by Category Pivot","description":"Numeric precision comparisons — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot for supplied numeric precision comparisons records (source_value, transformed_value). 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-20-178?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","source_value","transformed_value"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"transformed_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_value":10,"dataset_group":"group-a","transformed_value":1},{"date":"2026-10-02","row_id":"row-2","source_value":20,"dataset_group":"group-b","transformed_value":2},{"date":"2026-10-03","row_id":"row-3","source_value":15,"dataset_group":"group-a","transformed_value":3},{"date":"2026-10-04","row_id":"row-4","source_value":30,"dataset_group":"group-b","transformed_value":4}],"maxItems":200,"minItems":1},"field":{"enum":["source_value","transformed_value"],"type":"string","default":"source_value"}}},"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_F2wW-IlhWGbx6RzPxUSZu","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":"Runs two local analytical reports on supplied numeric precision comparison records: IQR-based outlier flagging and a date-by-category pivot table, for up to 200 rows.","exampleAgentPrompt":"I have 150 rows of source-value vs transformed-value comparison records across groups like 'group-a' and 'group-b' with dates — can you flag the IQR outliers and also pivot the data by date and category for source_value?","exampleUseCases":[{"title":"ETL pipeline transformation audit","prompt":"I just ran a data transformation job and have 120 rows with source_value and transformed_value per record, grouped by pipeline stage and dated by run date — flag any IQR outliers in transformed_value and give me a date-by-category pivot so I can spot which stages are drifting."},{"title":"Data quality check before reporting","prompt":"Before I publish my weekly metrics report, can you analyze these 80 comparison records — each has a source_value, transformed_value, a dataset_group, and a date — flag outliers using IQR on source_value and pivot the results by date and group?"},{"title":"Detect anomalies in sensor calibration data","prompt":"I have calibration readings for two sensor groups across 60 dates, stored as source_value and transformed_value pairs — please run IQR outlier detection on transformed_value and generate a date-by-category pivot so I can see which days and groups have anomalies."}],"resultDescription":"Returns two analytical reports: (1) IQR outlier flags identifying which rows have values outside the interquartile range for the selected field, and (2) a date-by-category pivot table aggregating the numeric comparison data by date and dataset_group — all computed locally from the supplied rows with no external data access.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, source_value, transformed_value) cause validation errors","Date strings not matching YYYY-MM-DD pattern will fail schema validation","Numeric values outside ±1,000,000,000,000 range will be rejected","All-null values for the selected field may produce empty or degenerate IQR results","Insufficient row count for meaningful IQR computation may yield trivial outlier flags"],"whenToPreferThis":"Choose this endpoint when you need both IQR outlier detection and a date-by-category pivot in a single low-cost call on a batch of up to 200 numeric comparison records (source vs transformed values). It is ideal for ETL validation, data quality audits, and transformation pipeline reviews where you need statistical anomaly flags alongside a temporal-categorical summary. It does not call external APIs or make predictions — all analysis is local and deterministic.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:25.071Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-iqr-outlier-flags-date-by-category-pivot-9e16a06e"}