替换已弃用的软件的独特挑战 funs()

Question

问题：

我有一个纯粹由数字数据类型的变量组成的 DataFrame。我有一个过去做得很好的例程，它检查 DataFrame 中的每个变量的统计异常值，并用 NA 值替换任何已识别的异常值。但是，此例程使用了最近被软弃用的 funs()。

研究过这个问题，我知道你应该能够基本上用 list(~ example_func()) 替换 funs() 例如：

>funs(mean(., trim = .2), median(., na.rm = TRUE))
>
>Would become:
>
>list(~ mean(., trim = .2), ~ median(., na.rm = TRUE))

很遗憾，这种补救措施不适用于我的用例。

功能正常，但现在已软弃用的代码：

以下代码有效，如下所示（对于具有异常值的变量，异常值将替换为 NA 值）；但是，它会触发关于现已软弃用的 funs() 的警告：

> # Which variables have missing values
> sapply(training_imptd, function(x) sum(is.na(x)))
           INDEX      TARGET_WINS   TEAM_BATTING_H  TEAM_BATTING_2B  TEAM_BATTING_3B 
               0                0                0                0                0 
 TEAM_BATTING_HR  TEAM_BATTING_BB  TEAM_BATTING_SO  TEAM_BASERUN_SB  TEAM_BASERUN_CS 
               0                0              102              131              772 
TEAM_BATTING_HBP  TEAM_PITCHING_H TEAM_PITCHING_HR TEAM_PITCHING_BB TEAM_PITCHING_SO 
            2085                0                0                0              102 
 TEAM_FIELDING_E TEAM_FIELDING_DP 
               0              286 
> 
> # Identify outliers and set them to NA (NAs to be fixed in next step by mice)
> training_imptd <- training_imptd %>%
+   mutate_all(
+     funs(ifelse(. %in% boxplot.stats(training_imptd$.)$out, NA, .))
+   )
>
> Warning: funs() is soft deprecated as of dplyr 0.8.0
> Please use a list of either functions or lambdas: 
> 
>   # Simple named list: 
>   list(mean = mean, median = median)
> 
>   # Auto named with `tibble::lst()`: 
>   tibble::lst(mean, median)
> 
>   # Using lambdas
>   list(~ mean(., trim = .2), ~ median(., na.rm = TRUE))
> This warning is displayed once per session. 
>
> # Which variables have missing values (after imputing NA for outliers)
> sapply(training_imptd, function(x) sum(is.na(x)))
           INDEX      TARGET_WINS   TEAM_BATTING_H  TEAM_BATTING_2B  TEAM_BATTING_3B 
               0               32               67               15               29 
 TEAM_BATTING_HR  TEAM_BATTING_BB  TEAM_BATTING_SO  TEAM_BASERUN_SB  TEAM_BASERUN_CS 
               0              129              102              252              827 
TEAM_BATTING_HBP  TEAM_PITCHING_H TEAM_PITCHING_HR TEAM_PITCHING_BB TEAM_PITCHING_SO 
            2086              213                4               90              140 
 TEAM_FIELDING_E TEAM_FIELDING_DP 
             303              318 

应该有效但无效的修正代码：

根据我所读到的关于用 list(~ example_func()) 替换 funs() 的内容，我希望以下代码的执行与上面利用 funs() 的代码完全相同，但事实并非如此（对于具有异常值的变量，异常值不会替换为 NA 值）：

> # Which variables have missing values
> sapply(training_imptd, function(x) sum(is.na(x)))
           INDEX      TARGET_WINS   TEAM_BATTING_H  TEAM_BATTING_2B  TEAM_BATTING_3B 
               0                0                0                0                0 
 TEAM_BATTING_HR  TEAM_BATTING_BB  TEAM_BATTING_SO  TEAM_BASERUN_SB  TEAM_BASERUN_CS 
               0                0              102              131              772 
TEAM_BATTING_HBP  TEAM_PITCHING_H TEAM_PITCHING_HR TEAM_PITCHING_BB TEAM_PITCHING_SO 
            2085                0                0                0              102 
 TEAM_FIELDING_E TEAM_FIELDING_DP 
               0              286 
> 
> # Identify outliers and set them to NA (NAs to be fixed in next step by mice)
> training_imptd <- training_imptd %>%
+   mutate_all(
+     list(~ ifelse(. %in% boxplot.stats(training_imptd$.)$out, NA, .))
+   )
> 
> # Which variables have missing values (after imputing NA for outliers)
> sapply(training_imptd, function(x) sum(is.na(x)))
           INDEX      TARGET_WINS   TEAM_BATTING_H  TEAM_BATTING_2B  TEAM_BATTING_3B 
               0                0                0                0                0 
 TEAM_BATTING_HR  TEAM_BATTING_BB  TEAM_BATTING_SO  TEAM_BASERUN_SB  TEAM_BASERUN_CS 
               0                0              102              131              772 
TEAM_BATTING_HBP  TEAM_PITCHING_H TEAM_PITCHING_HR TEAM_PITCHING_BB TEAM_PITCHING_SO 
            2085                0                0                0              102 
 TEAM_FIELDING_E TEAM_FIELDING_DP 
               0              286 

Answer 1

从函数内部删除不必要的training_imptd$。代词. 已经指代“当前列”，所以可以直接将其传递给boxplot.stats()：

training_imptd %>%
  mutate_all(
    ~ifelse(. %in% boxplot.stats(.)$out, NA, .)
  )