{"uid":"cap__27SEQM8LtADCYXAnMowE","slug":"company-headcount-observations-numeric-row-ordering-explicit-missing-155a67b1","name":"Company Headcount Observations — Numeric Row Ordering + Explicit Missing-Value Fill","description":"Company headcount observations — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied company headcount observations records (headcount, open_roles). 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-12-124?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","headcount","open_roles"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"headcount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"open_roles":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","headcount":10,"open_roles":1,"company_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","headcount":20,"open_roles":2,"company_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","headcount":15,"open_roles":3,"company_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","headcount":30,"open_roles":4,"company_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["headcount","open_roles"],"type":"string","default":"headcount"},"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_Y9FtGSp8tWDNwSlmO16-w","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":"Sorts company headcount observation rows numerically and fills missing values in headcount or open_roles fields using zero, mean, or median imputation — up to 200 rows, two analytical reports per call.","exampleAgentPrompt":"I have a list of up to 50 company headcount observations with some missing headcount values — can you sort the rows numerically and fill in the missing headcount entries using median imputation?","exampleUseCases":[{"title":"Fill missing headcount for HR reporting","prompt":"I have monthly headcount snapshots for two company groups, group-a and group-b, but several rows have null headcount values — please sort them by row number and fill those gaps using the median so I can use the data in my report."},{"title":"Impute open roles with zero for budget model","prompt":"My workforce dataset has rows with missing open_roles values across several dates and company groups. Can you order the rows numerically and fill all the nulls with zero so I can feed it into our budget model?"},{"title":"Clean headcount time series with mean fill","prompt":"I've got about 120 daily headcount observation records for our company, some with missing headcount numbers. Sort them and fill the blanks using mean imputation — I need two clean analytical reports back."}],"resultDescription":"Returns two analytical reports covering the submitted company headcount observation records (up to 200 rows), with rows numerically ordered by row_id and missing values in the specified field (headcount or open_roles) filled using the chosen method (zero, mean, or median). No external data is fetched or predicted.","failureModes":["More than 200 rows submitted — exceeds maxItems limit","Row missing required fields (row_id, company_group, date, headcount, or open_roles schema keys)","Invalid date format (must match YYYY-MM-DD pattern)","Invalid enum value for field or method parameters","Empty rows array (minItems: 1 violated)","Payment not included or insufficient (requires 0.01 USDC via x402)"],"whenToPreferThis":"Choose this endpoint when you have tabular company headcount or open_roles observations (up to 200 rows) that need numeric row ordering combined with explicit missing-value imputation (zero, mean, or median), and you want two structured analytical reports back without any live data lookup or external prediction. It is purpose-built for offline data cleaning of HR workforce metrics rather than general-purpose data transformation.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:33.241Z","isFirstParty":false,"canonicalSlug":"company-headcount-observations-numeric-row-ordering-explicit-missing-155a67b1"}