{"uid":"cap_7fbQfhXLo0_HnipfkqWNT","slug":"numeric-precision-comparisons-grouped-summary-daily-sum-series-f27bdf61","name":"Numeric Precision Comparisons — Grouped Summary & Daily Sum Series Analytics","description":"Numeric precision comparisons — Grouped numeric summary + Daily sum series: Grouped numeric summary + Daily sum series 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-20-089?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_sh251yaLqFVZ6spL--LFh","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":"Generates two analytical reports from user-supplied numeric precision comparison rows: a grouped summary and a daily sum time series, using local analytical engines.","exampleAgentPrompt":"Run two reports on my precision comparison data — a grouped numeric summary and a daily sum series — using source_value as the field. Here are my rows: group-a has row-1 on 2026-10-01 with source 10 and transformed 1, row-3 on 2026-10-03 with source 15 and transformed 3; group-b has row-2 on 2026-10-02 with source 20 and transformed 2, row-4 on 2026-10-04 with source 30 and transformed 4.","exampleUseCases":[{"title":"ETL pipeline transformation audit","prompt":"I have 50 rows from our ETL run — each has a source_value and transformed_value tagged by dataset_group and date. Can you generate a grouped numeric summary and a daily sum series so I can see where precision is being lost in the transformation? Use source_value as the field."},{"title":"Daily revenue reconciliation by product line","prompt":"Here are 120 comparison records with original and adjusted revenue figures per product group and date. Give me a grouped summary and a daily sum series using transformed_value so I can reconcile the adjustments."},{"title":"A/B test numeric output comparison","prompt":"I'm comparing model output scores (source_value) against human-labeled scores (transformed_value) across two groups and four days. Can you run both a grouped summary and a daily sum series on this dataset using source_value?"}],"resultDescription":"Two independent analytical reports: (1) a grouped numeric summary aggregating source_value or transformed_value statistics by dataset_group, and (2) a daily sum series showing totals by date — both computed from the supplied rows using local analytical engines, up to 200 rows per call.","failureModes":["Missing required fields (row_id, dataset_group, date, source_value, transformed_value) causes validation error","Date strings not matching YYYY-MM-DD pattern are rejected","Exceeding 200 rows returns an error or truncated result","Null values in source_value or transformed_value may affect aggregate computations","Invalid field enum value (not 'source_value' or 'transformed_value') causes request rejection","Payment failure via x402 protocol blocks execution"],"whenToPreferThis":"Choose this endpoint when you have a structured dataset of up to 200 numeric comparison rows (source vs. transformed values) and need both a grouped categorical summary and a daily sum time series in a single low-cost call ($0.01 USDC). Prefer this over generic analytics tools when you want a bundled two-report output without setting up a full analytics pipeline.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:39:08.153Z","isFirstParty":false,"canonicalSlug":"numeric-precision-comparisons-grouped-summary-daily-sum-series-f27bdf61"}