{"uid":"cap_Sv7OOqVu2P7HZh_hA7NfH","slug":"time-entries-explicit-missing-value-fill-51ba92e9","name":"Time Entries — Explicit Missing-Value Fill","description":"Time entries - Explicit missing-value fill: Explicit missing-value fill for Time entries. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded explicit missing-value fill deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-analytics-time-entries-fill-missing?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","project","date","hours","billable_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"project":{"type":"string","default":"","maxLength":80},"billable_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","hours":10,"row_id":"row-1","project":"group-a","billable_hours":1},{"date":"2026-10-02","hours":20,"row_id":"row-2","project":"group-b","billable_hours":2},{"date":"2026-10-03","hours":15,"row_id":"row-3","project":"group-a","billable_hours":3},{"date":"2026-10-04","hours":30,"row_id":"row-4","project":"group-b","billable_hours":4}],"maxItems":200,"minItems":1},"field":{"enum":["hours","billable_hours"],"type":"string","default":"hours"},"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_avXSzpeSGHVJF_m8N5u5F","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":"Fills missing numeric values (hours or billable_hours) in time entry records using zero, mean, or median imputation, returning up to 200 cleaned rows.","exampleAgentPrompt":"I have up to 200 time entry rows with some null 'hours' values — can you fill the missing ones using the median of the non-null values across the dataset?","exampleUseCases":[{"title":"Clean timesheet before payroll export","prompt":"I have a batch of employee timesheet rows where some 'hours' fields are null — fill them with the median so I can run payroll without errors."},{"title":"Fix billing data with zero imputation","prompt":"My billing export has several rows where 'billable_hours' is missing. Can you replace all the nulls with zero so the invoice totals don't break?"},{"title":"Impute project hours using mean for reporting","prompt":"Before I generate this week's project utilization report, fill in any missing 'hours' values in my time entries using the mean of the other rows."}],"resultDescription":"Returns the supplied time entry records with null or missing values in the specified field (hours or billable_hours) replaced according to the chosen method (zero, mean, or median). The result is a cleaned array of up to 200 typed records ready for downstream processing, billing, or reporting.","failureModes":["Empty rows array or minItems violation returns a validation error","rows array exceeds 200 items (maxItems limit) returns an error","Invalid date format (not YYYY-MM-DD pattern) causes row-level validation failure","Unknown method value outside zero/mean/median enum returns a schema error","Unknown field value outside hours/billable_hours enum returns a schema error","All values for the target field are null — mean/median imputation may return zero or an error","row_id missing or empty string causes required-field validation failure"],"whenToPreferThis":"Choose this endpoint when you have time entry records with null or missing numeric fields (hours or billable_hours) and need a quick, local imputation pass using zero, mean, or median fill before downstream billing, payroll, or analytics. It handles up to 200 rows per call with no external dependencies or enrichment — ideal for lightweight data-quality cleanup steps in an automated pipeline.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T19:08:06.269Z","isFirstParty":false,"canonicalSlug":"time-entries-explicit-missing-value-fill-51ba92e9"}