{"uid":"cap_gRFpk34wgP02OXukafVqJ","slug":"customer-segment-observations-numeric-distribution-numeric-interval-b61d8fa2","name":"Customer Segment Observations — Numeric Distribution + Numeric Interval Filter","description":"Customer segment observations — Numeric distribution + Numeric interval filter: Numeric distribution + Numeric interval filter for supplied customer segment observations records (account_count, revenue_amount). 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-company-16-074?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","account_count","revenue_amount"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"account_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"revenue_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","account_count":10,"company_group":"group-a","revenue_amount":1},{"date":"2026-10-02","row_id":"row-2","account_count":20,"company_group":"group-b","revenue_amount":2},{"date":"2026-10-03","row_id":"row-3","account_count":15,"company_group":"group-a","revenue_amount":3},{"date":"2026-10-04","row_id":"row-4","account_count":30,"company_group":"group-b","revenue_amount":4}],"maxItems":200,"minItems":1},"field":{"enum":["account_count","revenue_amount"],"type":"string","default":"account_count"},"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_wHsvPN36gn2_eBCKbu9xB","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 numeric distribution and applies a numeric interval filter on customer segment observation records (account_count, revenue_amount) for up to 200 rows, returning 2 analytical reports.","exampleAgentPrompt":"Analyze the numeric distribution and apply an interval filter on my customer segment data — here are up to 50 rows with row_id, company_group, date, account_count, and revenue_amount fields — run both reports on the revenue_amount field with a minimum of 500 and maximum of 50000.","exampleUseCases":[{"title":"Revenue distribution across company groups","prompt":"I have 120 rows of customer segment observations with company_group, date, account_count, and revenue_amount. Can you give me the numeric distribution of revenue_amount and also filter to only show me rows where revenue_amount falls between 1000 and 25000?"},{"title":"Account count interval filtering for a sales team","prompt":"I need two reports on my customer segment data: a distribution of account_count values and a filter showing only segments where account_count is between 5 and 100. I have about 80 rows with row_id, company_group, date, account_count, and revenue_amount."},{"title":"Segment outlier detection by revenue range","prompt":"Can you run a numeric distribution and an interval filter on these 200 customer segment records? I want to focus on the revenue_amount field and flag everything outside the range of 0 to 500000 — use the account_count and revenue_amount columns from my dataset."}],"resultDescription":"Returns 2 analytical reports: (1) a numeric distribution summarizing the spread and frequency of values in the selected field (account_count or revenue_amount), and (2) a numeric interval filter report listing rows whose selected field value falls within the specified minimum–maximum range. Results cover up to 200 input rows and are computed locally without any external lookup or prediction.","failureModes":["Input array exceeds 200 rows — request will be rejected or truncated","Missing required fields (row_id, company_group, date, account_count, revenue_amount) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers pattern validation failure","Minimum value greater than maximum value may produce empty interval filter results","Null values in the selected numeric field may be excluded from distribution and filter reports","Field enum value not matching 'account_count' or 'revenue_amount' causes schema rejection"],"whenToPreferThis":"Choose this endpoint when you have customer segment observation data (with account_count and revenue_amount fields) and need both a distribution summary and an interval/range filter in a single low-cost call. It is ideal for quick offline analytics on batches up to 200 rows without requiring external data enrichment, live lookups, or predictions. Prefer this over general-purpose analytics platforms when you want a cheap, deterministic, two-report output specifically tailored to company-group segment data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T12:48:36.596Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-numeric-distribution-numeric-interval-b61d8fa2"}