R dplyr从具有列名的列中选择值以在单独的列中进行选择 [英] R dplyr choose value from column with column name to choose in a separate column

问题描述

我有一个数据框，其中包含不同的数据列（例如x，y，z），另一列指定了要选择的列。我想使用dplyr :: mutate（或类似方法）制作一个新列，该列的值对应于选择指定的列中的值。但我想将所有列都放在首位。在我的真实数据中，我还有其他一些带有元数据的列。

Hi I have a data frame with different data columns (say x, y, z ) and another column which specifies which one to choose. I want to use dplyr::mutate (or similar) to make a new column that has the value corresponding to value in the column specified by "choose". But I want to keep all the columns in the first place. In my real data I also have a few other columns with metadata.

示例数据：

library(dplyr)
testdf <- data.frame(x = 1:5, y = 11:15, z = 101:105, choose = c("z","y","x","y","z"))

在我的示例中，可以使用 case_when ，但是在我的实际脚本中，会生成列名和select列，并且它们可能具有不同的值，所以我不想对可能存在的名称进行硬编码。

I can make this work in my example using case_when but in my actual script the column names and choose column are generated and may have different values, so I don't want to hardcode what names there could be.

所需的输出/测试

mutate(testdf, selectedValue = case_when(choose == "x" ~x,
                                     choose == "y"~ y,
                                     choose == "z"~ z, T~NA_integer_))

#>   x  y   z choose selectedValue
#> 1 1 11 101      z           101
#> 2 2 12 102      y            12
#> 3 3 13 103      x             3
#> 4 4 14 104      y            14
#> 5 5 15 105      z           105

^{由 reprex软件包（v0.3.0）}

^{Created on 2019-09-18 by the reprex package (v0.3.0)}

推荐答案

这是data.table解决方案。在这种情况下，我认为dplyr解决方案不比其他解决方案（特别是基于r和data.table）更具可读性。

Here is a data.table solution. This is a case where I don't think the dplyr solutions are more human readable than other solutions (base r and data.table specifically).

library(data.table)
testdt <- data.table(x = 1:5, y = 11:15, z = 101:105, choose = c("z","y","x","y","z"))
testdt[,selectedValue := get(choose), by = choose]
testdt
#>    x  y   z choose selectedValue
#> 1: 1 11 101      z           101
#> 2: 2 12 102      y            12
#> 3: 3 13 103      x             3
#> 4: 4 14 104      y            14
#> 5: 5 15 105      z           105

^{由 reprex包（v0.3.0）}

^{Created on 2019-09-17 by the reprex package (v0.3.0)}

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