{"uid":"cap_L9lpZQbCiEjJppauX3b9e","slug":"customer-segment-observations-category-frequencies-explicit-missing-ec2f058b","name":"Customer Segment Observations: Category Frequencies + Explicit Missing-Value Fill","description":"Customer segment observations — Category frequencies + Explicit missing-value fill: Category frequencies + Explicit missing-value fill 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-16-112?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_Aju1COS0o2mVT50Ka2BnV","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 category frequency distributions and fills missing values (via zero, mean, or median) for customer segment observation records containing account_count and revenue_amount fields.","exampleAgentPrompt":"I have up to 200 rows of customer segment data with company_group, date, account_count, and revenue_amount — can you run category frequency analysis and fill any missing revenue_amount values using the median, and give me both reports?","exampleUseCases":[{"title":"Segment frequency audit for sales team","prompt":"I've got a list of customer segment records by company group with account counts and revenue amounts — can you tell me how often each company group appears (category frequencies) and fill any missing account_count values with the mean? Here are the rows: group-a, group-b, group-a, null for group-c."},{"title":"Data quality check before dashboard import","prompt":"Before I import this dataset into our dashboard, can you run the category frequency report on company_group and replace any null revenue_amount entries with zero across these 150 customer segment observation rows?"},{"title":"Revenue imputation for quarterly reporting","prompt":"I need to prep our quarterly segment report — please analyze the frequency distribution of company groups and fill all missing revenue_amount values using the median imputation method for these customer segment records."}],"resultDescription":"Returns two analytical reports: (1) a category frequency table showing how often each company_group value appears across the submitted rows, and (2) a dataset with missing values in the specified numeric field (account_count or revenue_amount) explicitly filled using the chosen method (zero, mean, or median). Both reports are computed locally without external lookups.","failureModes":["Input exceeds 200 rows — request will be rejected","Missing required fields (row_id, company_group, date, account_count, or revenue_amount) cause validation errors","Invalid date format (not YYYY-MM-DD) causes schema rejection","Numeric values outside [-1,000,000,000,000, 1,000,000,000,000] range are rejected","Unsupported fill method enum value causes error","Empty rows array returns validation error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of customer segment data and need both a category frequency breakdown and missing-value imputation in a single low-cost ($0.01 USDC) call. It is ideal for lightweight, local data quality and distribution analysis on account_count or revenue_amount fields without requiring an external ML service or database lookup. Prefer alternatives if you need predictions, live data enrichment, or more than 200 rows processed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T12:48:36.843Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-category-frequencies-explicit-missing-ec2f058b"}