{"uid":"cap_lbiiOtOw6cyvJRI7P4HnO","slug":"numeric-precision-comparisons-category-frequencies-numeric-interval-fe1f95e5","name":"Numeric Precision Comparisons — Category Frequencies + Numeric Interval Filter","description":"Numeric precision comparisons — Category frequencies + Numeric interval filter: Category frequencies + Numeric interval filter 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-20-101?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_aHCW2b8KH-wQDLno05DgY","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 rows of source/transformed numeric pairs, producing category frequency counts by dataset group and a filtered subset of rows within a specified numeric interval — two independent analytical reports in one call.","exampleAgentPrompt":"I have up to 200 rows of source and transformed numeric values with dataset groups — can you give me a category frequency breakdown by group AND filter the rows where source_value falls between 0 and 100, using these records: row-1 group-a 2026-10-01 source=10 transformed=1, row-2 group-b 2026-10-02 source=20 transformed=2?","exampleUseCases":[{"title":"ETL pipeline numeric validation audit","prompt":"I've run a data transformation job and want to check how the values changed — give me frequency counts of each dataset group and filter to only the rows where transformed_value is between 1 and 50, using these 150 rows of source and transformed pairs."},{"title":"Quality control interval outlier detection","prompt":"Can you analyze my sensor readings and tell me how many records fall in each category group, and also which rows have source_value between -500 and 500? I have 80 rows with row IDs, dates, group labels, source readings, and transformed readings."},{"title":"A/B test numeric range segmentation","prompt":"I have two experiment groups with numeric scores before and after normalization — show me the frequency breakdown by group and filter to rows where source_value is between 10 and 90 so I can see which are in the mid-range band."}],"resultDescription":"Returns two independent reports: (1) a frequency table showing how many rows belong to each dataset_group category, and (2) a filtered list of rows where the selected numeric field (source_value or transformed_value) falls within the specified minimum–maximum interval. Up to 200 input rows supported per call.","failureModes":["Empty or missing rows array returns an error","More than 200 rows in the input exceeds the limit","Invalid date format (not YYYY-MM-DD) fails schema validation","Numeric values outside ±1,000,000,000,000 are rejected","minimum greater than maximum produces an empty interval filter result","Missing required row fields (row_id, dataset_group, date) cause validation failure"],"whenToPreferThis":"Choose this endpoint when you need both a categorical frequency summary AND a numeric range filter applied to the same dataset of source/transformed numeric pairs in a single low-cost API call. It is ideal for ETL validation, data transformation QA, or any scenario where you want to understand group distribution and isolate records in a value band simultaneously. Prefer this over separate analytics tools when your dataset is under 200 rows and you want a lightweight, offline computation at $0.01 per call with no external data dependencies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:25.070Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-category-frequencies-numeric-interval-fe1f95e5"}