根据 R 数据帧中的两个条件进行变异

Question

我有一个可以从下面的代码生成的 R 数据框

DF <- data.frame("Person_id" = c(1,1,1,1,2,2,2,2,3,3), "Type" = c("IN","OUT","IN","ANC","IN","OUT","IN","ANC","EM","ANC"), "Name" = c("Nara","Nara","Nara","Nara","Dora","Dora","Dora","Dora","Sara","Sara"),"day_1" = c("21/1/2002","21/4/2002","21/6/2002","21/9/2002","28/1/2012","28/4/2012","28/6/2012","28/9/2012","30/06/2004","30/06/2005"),"day_2" = c("23/1/2002","21/4/2002","","","30/1/2012","28/4/2012","","28/9/2012","",""))

我想做的是根据下面给出的几个条件创建两个新列 admit_start_date 和 admit_end_date

规则 1

  admit_start_date = day_1
  admit_end_date   = day_2 (sometimes day_2 can be NA. So refer Rule 2 below)

规则 2

   if day_2 is (null or blank or na) and Type is (Out or ANC or EM) then 
         admit_end_date = day_1 
   else (if Type is IN)
         admit_end_date = day_1 + 5 (days)

这是我正在尝试但似乎没有帮助的方法

    transform_dates = function(DF){  # this function is to create 'date' columns  
  DF %>% 
    mutate(admit_start_date = day_1) %>% 
    mutate(admit_end_date = day_2) %>%
    admit_end_date = if_else(((Type == 'Out' & admit_end_date.isna() ==True|Type == 'ANC' & admit_end_date.isna() ==True|Type == 'EM' & admit_end_date.isna() ==True),day_1,day_1 + 5)
    )
}

如您所见，我不确定如何检查新创建的列的 NA 并将那些 NAs 替换为 day_1 或 day_1 + 5(days) 基于类型列。

你能帮忙吗？

我希望我的输出如下所示

Answer 1

将"day"列转换为实际日期对象后，我们可以使用case_when分别指定每个条件。

library(dplyr)

DF %>%
  mutate_at(vars(starts_with('day')), as.Date, "%d/%m/%Y") %>%
  mutate(admit_start_date = day_1, 
         admit_end_date = case_when(
         !is.na(day_2) ~day_2,
         is.na(day_2) & Type %in% c('OUT', 'ANC', 'EM') ~ day_1, 
         Type == 'IN' ~ day_1 + 5))


#  Person_id Type Name      day_1      day_2 admit_start_date admit_end_date
#1          1   IN Nara 2002-01-21 2002-01-23       2002-01-21     2002-01-23
#2          1  OUT Nara 2002-04-21 2002-04-21       2002-04-21     2002-04-21
#3          1   IN Nara 2002-06-21       <NA>       2002-06-21     2002-06-26
#4          1  ANC Nara 2002-09-21       <NA>       2002-09-21     2002-09-21
#5          2   IN Dora 2012-01-28 2012-01-30       2012-01-28     2012-01-30
#6          2  OUT Dora 2012-04-28 2012-04-28       2012-04-28     2012-04-28
#7          2   IN Dora 2012-06-28       <NA>       2012-06-28     2012-07-03
#8          2  ANC Dora 2012-09-28 2012-09-28       2012-09-28     2012-09-28
#9          3   EM Sara 2004-06-30       <NA>       2004-06-30     2004-06-30
#10         3  ANC Sara 2005-06-30       <NA>       2005-06-30     2005-06-30

dataframe 中的日期不是 class "Date", (class(DF$day_1))，使用 mutate_at 我们将它们的 class 更改为 "Date" 所以我们可以对其进行数学计算。 starts_with('day') 表示名称以 "day" 开头的任何列都将转换为 "Date" class。当我们想将相同的功能应用于多个列时，我们使用 mutate_at。

case_when 是嵌套 ifelse 语句的替代方法。它们按顺序执行。因此检查第一个条件，如果条件满足则不检查其余条件。如果不满足第一个条件，则检查第二个条件，依此类推。因此，这里不需要 else。如果none的条件都满足就returnsNA。检查 ?case_when。

根据 R 数据帧中的两个条件进行变异

Mutate based on two conditions in R dataframe

r

dataframe

lubridate

dplyr

tidyr