{"uid":"cap_1xFoO2XTYXvus3q4tWafO","slug":"company-headcount-observations-daily-sum-series-explicit-missing-297485e4","name":"Company Headcount Observations — Daily Sum Series + Explicit Missing-Value Fill","description":"Company headcount observations — Daily sum series + Explicit missing-value fill: Daily sum series + 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-12-145?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_5ahX1y1oMxF6hm_mKLlRO","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 daily sum aggregations and fills missing values (zero, mean, or median) in company headcount and open-roles observation data across up to 200 rows.","exampleAgentPrompt":"I have headcount and open_roles records for group-a and group-b across October 2026 — can you compute the daily sum series for headcount and fill any missing values using the median method? Here are up to 200 rows with row IDs, dates, and company groups.","exampleUseCases":[{"title":"HR daily headcount rollup","prompt":"I've got daily headcount snapshots for three company groups over Q3 — some days have null values. Can you compute the daily sum series for headcount and fill those gaps using median substitution? I'll provide up to 150 rows with row IDs, dates, and group labels."},{"title":"Open roles gap-fill for reporting","prompt":"Our open_roles data has missing entries on several dates across our business units. Can you run a daily sum aggregation on the open_roles field and fill missing values with zero so we get a complete daily series? I have about 80 rows covering group-a and group-b."},{"title":"Multi-group workforce trend analysis","prompt":"I need to summarize daily total headcount across all our company groups and use mean imputation to handle any nulls before the report goes out. Can you process these 200 rows of headcount observations dated from 2026-10-01 through 2026-12-31 and give me the daily sum series?"}],"resultDescription":"Returns two independent analytical reports: (1) a daily sum series aggregating the specified field (headcount or open_roles) by date and company group, and (2) an explicit missing-value fill replacing nulls with the chosen strategy (zero, mean, or median). Results cover up to 200 input rows.","failureModes":["Input rows exceed 200-item limit — request rejected","Date fields not matching YYYY-MM-DD pattern — validation error","Missing required fields (row_id, company_group, date) — schema validation failure","Numeric values outside allowed range (±1 trillion) — rejection","All values null for a group/date combination — fill output may be empty or zero-based"],"whenToPreferThis":"Choose this endpoint when you have structured company headcount or open-roles time series data (up to 200 rows) that needs daily sum aggregation combined with missing-value imputation in a single call. It is ideal for HR analytics, workforce reporting, or data preparation pipelines where both aggregation and gap-filling are needed together without external data lookups or live HR system integrations.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:35.414Z","isFirstParty":false,"canonicalSlug":"company-headcount-observations-daily-sum-series-explicit-missing-297485e4"}