R 使用变量名中的值重塑数据
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: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",
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