{"uid":"cap_1mOUFY6maZlsJIOuv4Ffj","slug":"delivery-timing-explicit-missing-value-fill-c5275db1","name":"Delivery Timing – Explicit Missing-Value Fill","description":"Delivery timing - Explicit missing-value fill: Explicit missing-value fill for Delivery timing. 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-delivery-timing-fill-missing?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","route","date","delivery_minutes","distance_km"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"route":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"distance_km":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"delivery_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","route":"group-a","row_id":"row-1","distance_km":1,"delivery_minutes":10},{"date":"2026-10-02","route":"group-b","row_id":"row-2","distance_km":2,"delivery_minutes":20},{"date":"2026-10-03","route":"group-a","row_id":"row-3","distance_km":3,"delivery_minutes":15},{"date":"2026-10-04","route":"group-b","row_id":"row-4","distance_km":4,"delivery_minutes":30}],"maxItems":200,"minItems":1},"field":{"enum":["delivery_minutes","distance_km"],"type":"string","default":"delivery_minutes"},"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_lQltdoq6AYzhz1z_RVY8t","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 (delivery_minutes or distance_km) in delivery timing records using zero, mean, or median imputation across up to 200 rows.","exampleAgentPrompt":"I have a batch of up to 200 delivery records with some missing delivery_minutes values — can you fill those nulls using the median of the other rows? The records include fields like route, date, distance_km, and delivery_minutes.","exampleUseCases":[{"title":"Clean logistics data before reporting","prompt":"I've got a CSV of delivery runs for last month and some of the delivery_minutes entries are null — can you fill those missing values using the median so I can run my on-time report without errors?"},{"title":"Zero-fill missing distances for route comparison","prompt":"Some of my delivery records are missing distance_km values. Can you fill all the nulls with zero so I can do a quick before/after comparison across route group-a and group-b?"},{"title":"Mean imputation for ML feature preparation","prompt":"Before I train my delivery delay model, I need to impute missing delivery_minutes in my dataset using the mean. I have about 150 rows with route, date, and distance_km already populated — can you fill the gaps?"}],"resultDescription":"A processed set of delivery timing records (up to 200) where null values in the specified field (delivery_minutes or distance_km) have been replaced with the chosen fill value (zero, mean, or median computed from the supplied data). No external data is used; all computation is local to the provided rows.","failureModes":["Input array is empty or exceeds 200 rows — rejected with validation error","Invalid date format (not YYYY-MM-DD) causes row rejection","Specified field not present or not nullable in input schema","All values in the target field are null — mean/median cannot be computed","row_id missing or empty — required field validation failure","Unsupported method enum value provided"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local missing-value imputation specifically for delivery timing datasets (delivery_minutes or distance_km) without external enrichment or forecasting. It is ideal for pre-processing small-to-medium batches (≤200 rows) before analytics, reporting, or ML pipelines, and when you want deterministic fill strategies (zero, mean, or median) with no side effects.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T19:09:59.585Z","isFirstParty":false,"canonicalSlug":"delivery-timing-explicit-missing-value-fill-c5275db1"}