Question

我有一个数据框，其中有几列具有可能的目标值（在我的示例中为value和value2以下），有些列具有预测值。这些列均以“ predMod”开头。现在，我想计算所有“ predMod”列之间的差异，即我的目标变量的值。

示例：

target = "value2"

       date    value value2 predModLM1 predModLM2
1  2015-07-01    NA      5   3.236827   3.291434
2  2015-07-02    NA      5   3.236827   3.291434
3  2015-07-03    NA      5   3.236827   3.291434
4  2015-07-04    NA      5   3.236827   3.291434
5  2015-07-05    NA      5   3.236827   3.291434
6  2015-07-06   3.4      5   3.236827   3.291434
7  2015-07-07   3.4      5   3.236827   3.291434
8  2015-07-08   3.4      5   3.236827   3.291434
9  2015-07-09   3.4      5   3.236827   3.291434
10 2015-07-10   3.4      5   3.236827   3.291434

现在应该计算出以“ predMod”开头的每一列与来自目标的“ value2”列之间的差异。

我可以做到：

results <- data %>%
select(date, target, contains("predMod")) %>%
mutate_at(. , vars(-c(date, target)), funs(residuals = . - value2))

结果：

         date value2 predModLM1 predModLM2 predModLM1_residuals   predModLM2_residuals
1  2015-07-01      5   3.236827   3.291434            -1.763173              -1.708566
2  2015-07-02      5   3.236827   3.291434            -1.763173            -1.708566
3  2015-07-03      5   3.236827   3.291434            -1.763173            -1.708566
4  2015-07-04      5   3.236827   3.291434            -1.763173            -1.708566
5  2015-07-05      5   3.236827   3.291434            -1.763173            -1.708566
6  2015-07-06      5   3.236827   3.291434            -1.763173            -1.708566
7  2015-07-07      5   3.236827   3.291434            -1.763173            -1.708566
8  2015-07-08      5   3.236827   3.291434            -1.763173            -1.708566
9  2015-07-09      5   3.236827   3.291434            -1.763173            -1.708566
10 2015-07-10      5   3.236827   3.291434            -1.763173            -1.708566

但是在我的解决方案中，将其硬编码为funs（-> funs（residuals =。-value2）。如果我将value2更改为target（-> funs（residuals =。-target），则整个操作将不起作用。 ..我该如何解决？

一个想法是用position参数替换value2。这样，目标值始终位于第2列中。但是我失败了：-（

非常感谢，马可

Answer 1

为此，我们需要将字符串转换为符号并进行求值（!!）

library(tidyverse)
data %>%
  select(date, target, contains("predMod")) %>%
  mutate_at(vars(-date, -target), funs(residuals = . - !! rlang::sym(target)))
#      date value2 predModLM1 predModLM2 predModLM1_residuals predModLM2_residuals
#1  2015-07-01      5   3.236827   3.291434            -1.763173            -1.708566
#2  2015-07-02      5   3.236827   3.291434            -1.763173            -1.708566
#3  2015-07-03      5   3.236827   3.291434            -1.763173            -1.708566
#4  2015-07-04      5   3.236827   3.291434            -1.763173            -1.708566
#5  2015-07-05      5   3.236827   3.291434            -1.763173            -1.708566
#6  2015-07-06      5   3.236827   3.291434            -1.763173            -1.708566
#7  2015-07-07      5   3.236827   3.291434            -1.763173            -1.708566
#8  2015-07-08      5   3.236827   3.291434            -1.763173            -1.708566
#9  2015-07-09      5   3.236827   3.291434            -1.763173            -1.708566
#10 2015-07-10      5   3.236827   3.291434            -1.763173            -1.708566

mutate_at与固定列的值组合

1 个答案: