dplyr ifelse声明中的嵌套条件

我使用dplyr和ifelse创建一个基于两个条件的新列，其数据如下。dplyr ifelse声明中的嵌套条件

dat <- structure(list(GenIndID = c("BHS_034", "BHS_034", "BHS_068", 
"BHS_068", "BHS_068", "BHS_068", "BHS_068", "BHS_068", "BHS_068", 
"BHS_068", "BHS_068"), IndID = c("BHS_034_A", "BHS_034_A", "BHS_068_A", 
"BHS_068_A", "BHS_068_A", "BHS_068_A", "BHS_068_A", "BHS_068_A", 
"BHS_068_A", "BHS_068_A", "BHS_068_A"), Fate = c("Mort", "Mort", 
"Alive", "Alive", "Alive", "Alive", "Alive", "Alive", "Alive", 
"Alive", "Alive"), Status = c("Alive", "Mort", "Alive", "Alive", 
"MIA", "Alive", "MIA", "Alive", "MIA", "Alive", "Alive"), Type = c("Linked", 
"Linked", "SOB", "SOB", "SOB", "SOB", "SOB", "SOB", "SOB", "SOB", 
"SOB"), SurveyID = c("GYA13-1", "GYA14-1", "GYA13-1", "GYA14-1", 
"GYA14-2", "GYA15-1", "GYA16-1", "GYA16-2", "GYA17-1", "GYA17-3", 
"GYA15-2"), SurveyDt = structure(c(1379570400, 1407477600, 1379570400, 
1407477600, 1409896800, NA, 1462946400, 1474351200, 1495519200, 
1507010400, 1441951200), tzone = "", class = c("POSIXct", "POSIXt" 
))), row.names = c(NA, 11L), .Names = c("GenIndID", "IndID", 
"Fate", "Status", "Type", "SurveyID", "SurveyDt"), class = "data.frame") 

> dat 
    GenIndID  IndID Fate Status Type SurveyID SurveyDt 
1 BHS_034 BHS_034_A Mort Alive Linked GYA13-1 2013-09-19 
2 BHS_034 BHS_034_A Mort Mort Linked GYA14-1 2014-08-08 
3 BHS_068 BHS_068_A Alive Alive SOB GYA13-1 2013-09-19 
4 BHS_068 BHS_068_A Alive Alive SOB GYA14-1 2014-08-08 
5 BHS_068 BHS_068_A Alive MIA SOB GYA14-2 2014-09-05 
6 BHS_068 BHS_068_A Alive Alive SOB GYA15-1  <NA> 
7 BHS_068 BHS_068_A Alive MIA SOB GYA16-1 2016-05-11 
8 BHS_068 BHS_068_A Alive Alive SOB GYA16-2 2016-09-20 
9 BHS_068 BHS_068_A Alive MIA SOB GYA17-1 2017-05-23 
10 BHS_068 BHS_068_A Alive Alive SOB GYA17-3 2017-10-03 
11 BHS_068 BHS_068_A Alive Alive SOB GYA15-2 2015-09-11

更具体地说，GenIndID分组我想要一个新的日期字段是基于两个条件语句为Type和Fate最大SurveyDt。此外，我希望最大日期仅在Status == Alive时评估SurveyDt。我的代码如下生成所有NA值，而不是所有符合所有指定条件的BHS_068的描述日期字段。

我最近看到case_when这可能适合在这里，但我无法正确实施它。

dat %>% group_by(GenIndID) %>% 
    mutate(NewDat = as.POSIXct(ifelse(Type == "SOB" & Fate == "Alive", max(SurveyDt[Status == "Alive"], na.rm = F), NA), 
          origin='1970-01-01', na.rm=T)) %>% 
    as.data.frame()

任何意见，将不胜感激。

来源

2017-10-11 B. Davis

你能提供出所需的输出如何看起来像一个桌子？ – Cris

如果您想坚持使用dplyr并使用case_when您必须确保每个case语句的值都是相同的类型。

在这种情况下，您的TRUE值将是datetime，因此您必须将默认值设置为datetime，并将其包装在as.POSIXct中。

dat %>% 
    group_by(GenIndID) %>% 
    mutate(NewDat = case_when(Type == "SOB" & Fate == "Alive" ~ max(SurveyDt[Status == "Alive"], na.rm = TRUE), 
          TRUE ~ as.POSIXct(NA, origin = "1970-01-01")))

使用ifelse

dat %>% 
    group_by(GenIndID) %>% 
    mutate(NewDat = ifelse(Type == "SOB" & Fate == "Alive", 
         max(SurveyDt[Status == "Alive"], na.rm = TRUE), 
         as.POSIXct(NA, origin = "1970-01-01")))

来源

2017-10-11 20:04:54

因为我更熟悉该语法，所以如果ifelse可能会出现相同的结果，那么我不会绑定到'case_when'。 –

对于'case_when'是'TRUE〜as.POSIXct（NA，origin =“1970-01-01”''提供'ifelse'的else部分？也就是说，对于指定条件没有得到满足，我无法从帮助文件中解释这一点（用我的能力......）。 –

我们可以使用data.table。在转换为data.table（setDT(dat)）后，指定i作为逻辑比较，按'GenIndID'分组，我们将'SurveyDt'的max分配给'NewDat'，'Status'为'NewDat'

library(data.table) 
setDT(dat)[Type == "SOB" & Fate == "Alive", 
     NewDat := max(SurveyDt[Status == "Alive"], na.rm = TRUE), GenIndID]

来源

2017-10-11 19:57:41 akrun

dplyr ifelse声明中的嵌套条件

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