R 使用变量名中的值重塑数据

R 使用变量名中的值重塑数据,r,reshape,tidyr,R,Reshape,Tidyr,我有一个非常广泛的dataset 2000+变量,我正在尝试整理这些变量,但我在尝试从变量名中提取一个值时遇到了困难。如果我有一个变量是E1Time1\u Date,我想将它重新设置为三个变量:E=1、Time=1和Date=原始日期值 这可能吗?我尝试过使用“聚集”,但我猜我需要先做一步,但我错过了这一步。谢谢你的帮助 如果有人想实现这一奇迹,这里有一个示例数据集: structure(list(ID = c(123, 225), UnrelatedV1 = c("Unrelated1",

我有一个非常广泛的dataset 2000+变量,我正在尝试整理这些变量,但我在尝试从变量名中提取一个值时遇到了困难。如果我有一个变量是E1Time1\u Date,我想将它重新设置为三个变量:E=1、Time=1和Date=原始日期值

这可能吗?我尝试过使用“聚集”,但我猜我需要先做一步,但我错过了这一步。谢谢你的帮助

如果有人想实现这一奇迹,这里有一个示例数据集:

structure(list(ID = c(123, 225), UnrelatedV1 = c("Unrelated1", 
"Unrelated1"), UnrelatedV2 = c("Unrelated2", "Unrelated2"), E1T1_Date = structure(c(1506816000, 
1513296000), class = c("POSIXct", "POSIXt"), tzone = "UTC"), 
    E1T1_v1 = c(10, 20), E1T1_v2 = c(20, 20), E1T1_v3 = c(30, 
    20), E1T1_v4 = c(40, 20), E1T2_Date = structure(c(1512086400, 
    NA), class = c("POSIXct", "POSIXt"), tzone = "UTC"), E1T2_v1 = c(10, 
    NA), E1T2_v2 = c(10, NA), E1T2_v3 = c(10, NA), E1T2_v4 = c(10, 
    NA), E2T1_Date = structure(c(1522540800, 1525132800), class = c("POSIXct", 
    "POSIXt"), tzone = "UTC"), E2T1_v1 = c(10, 20), E2T1_v2 = c(20, 
    20), E2T1_v3 = c(10, 20), E2T1_v4 = c(10, 20), E2T2_Date = structure(c(1533859200, 
    NA), class = c("POSIXct", "POSIXt"), tzone = "UTC"), E2T2_v1 = c(10, 
    NA), E2T2_v2 = c(30, NA), E2T2_v3 = c(10, NA), E2T2_v4 = c(10, 
    NA)), .Names = c("ID", "UnrelatedV1", "UnrelatedV2", "E1T1_Date", 
"E1T1_v1", "E1T1_v2", "E1T1_v3", "E1T1_v4", "E1T2_Date", "E1T2_v1", 
"E1T2_v2", "E1T2_v3", "E1T2_v4", "E2T1_Date", "E2T1_v1", "E2T1_v2", 
"E2T1_v3", "E2T1_v4", "E2T2_Date", "E2T2_v1", "E2T2_v2", "E2T2_v3", 
"E2T2_v4"), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-2L))

看起来您混合了数字和日期值,这会使收集变得有点棘手。一种方法是现在将日期转换为数字,然后一旦转换为最终格式,就可以将日期更改回原来的格式。这应该让你开始

library(tidyverse)
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    -2L))
data %>%  
  #convert dates to numeric so we can gather them in the same column
  mutate_if(is.POSIXct, as.integer) %>%
  gather(-ID, -contains("Unrelated"), key = variable, value = value) %>% 

  #add an underscore between E and T to make separating them easier
  mutate(loc = gregexpr("T", variable)[[1]],
         variable = paste0(substr(variable, 1, loc - 1), "_",
                           substr(variable, loc, nchar(variable)))) %>% 
  select(-loc) %>% 

  #separate into three distinct columns
  separate(variable, into = c("E", "T", "vDate"), sep = "_")

# A tibble: 40 x 7
ID      UnrelatedV1 UnrelatedV2     E     T vDate      value
<dbl>       <chr>       <chr>   <chr> <chr> <chr>      <dbl>
1   123  Unrelated1  Unrelated2    E1    T1  Date 1506816000
2   225  Unrelated1  Unrelated2    E1    T1  Date 1513296000
3   123  Unrelated1  Unrelated2    E1    T1    v1         10
4   225  Unrelated1  Unrelated2    E1    T1    v1         20
5   123  Unrelated1  Unrelated2    E1    T1    v2         20
6   225  Unrelated1  Unrelated2    E1    T1    v2         20
7   123  Unrelated1  Unrelated2    E1    T1    v3         30
8   225  Unrelated1  Unrelated2    E1    T1    v3         20
9   123  Unrelated1  Unrelated2    E1    T1    v4         40
10   225  Unrelated1  Unrelated2    E1    T1    v4         20

在dput中,有E1T1_v1、E1T1_v2等列。非常感谢!这很好,但我无法将日期转换回常规的日期格式。我最喜欢的as.Datedata$Date,%m/%d/%Y将所有日期转换为NA。日期以秒为单位,因此您需要将它们转换为天并指定起始日期。试试这个:as.Datedata$Date/24*60*60,origin=1970-01-01