首页 > 解决方案 > 基于地理空间和时间数据点估算缺失值

问题描述

我有以下数据框。

data.frame(stringsAsFactors = FALSE,
  Item = c("A","A", "B", "B","C"),
                       CITY = c("C1",
                                "C2","C3","C4", "C5"),
                        lat = c(23.1608938,
                                23.1608938,13.0836939,23,23.0216238),
                       long = c(79.9497702,
                                79.9497702,80.270186,74,72.5797068),
                      DATE = c("2019-04-12","2019-05-03","2019-06-28","2019-10-18",
                              "2019-12-23"),
                   BASIC_RATE = c(5445, 5445, 13380, 15000, 15000),
                   MIN_RATE = c(5150, 5150, NA, 5150, 5150),
                   MAX_RATE = c(5500, 5500, NA, 5500, 5500),
                     Region = as.factor(c("R1 ","R1 ", "R2 ","R3 ","R3 ")))

我的目标是根据按地区分组的地理空间(纬度和经度)和时间数据(日期)来估算 Min 和 Max Rates 中的缺失值。

为上述情况估算缺失值的任何推荐方法。

标签: rimputation

解决方案


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