Question

我最近开始尝试在tidyverse中完成所有代码。这有时使我陷入困境。这是我在tidyverse中无法完成的简单任务：我需要一个数据框中的列，该列从左返回第一个非na值的位置索引。有谁知道如何使用mutate在dplyr中实现这一目标？

这是所需的输出。

data.frame(                           
"X1"=c(100,rep(NA,8)),
"X2"=c(NA,10,rep(NA,7)),
"X3"=c(NA,NA,1000,1000,rep(NA,5)),
"X4"=c(rep(NA,4),25,50,10,40,50),
"FirstNonNaPosition"=c(1,2,3,3,4,4,4,4,4)
)

Answer 1

将base R元素替换为0后，max.col是一个更简单，有效的NA选项

max.col(replace(df2[1:4], is.na(df2[1:4]), 0), 'first')

甚至

df2$FirstNonNaPosition <- max.col(!is.na(df2[1:4]), "first")
df2$FirstNonNaPosition
#[1] 1 2 3 3 4 4 4 4 4

对于tidyverse，可能的选项是pmap

df2 %>% 
  mutate(FirstNonNaPosition = pmap_int(.[-5], ~ 
                          which.max(!is.na(c(...)))))

或包装max.col

df2 %>% 
   mutate(FirstNonNaPosition = max.col(!is.na(.[-5]), 'first'))

数据

df2 <- structure(list(X1 = c(100, NA, NA, NA, NA, NA, NA, NA, NA), X2 = c(NA, 
10, NA, NA, NA, NA, NA, NA, NA), X3 = c(NA, NA, 1000, 1000, NA, 
NA, NA, NA, NA), X4 = c(NA, NA, NA, NA, 25, 50, 10, 40, 50), 
    FirstNonNaPosition = c(1, 2, 3, 3, 4, 4, 4, 4, 4)), 
    class = "data.frame", row.names = c(NA, 
-9L))

Answer 2

还有base R的可能性：

apply(df, 1, which.max)

[1] 1 2 3 3 4 4 4 4 4

与dplyr相同：

df %>%
 mutate(FirstNonNaPosition = apply(., 1, which.max))

对@Andrew提到的方案的修改：

apply(df, 1, function(x) which.max(!is.na(x)))

与dplyr相同：

df %>%
 mutate(FirstNonNaPosition = apply(., 1, function(x) which.max(!is.na(x))))

Answer 3

您也可以使用apply：

data.frame(                           
"X1"=c(100,rep(NA,8)),
"X2"=c(NA,10,rep(NA,7)),
"X3"=c(NA,NA,1000,1000,rep(NA,5)),
"X4"=c(rep(NA,4),25,50,10,40,50),
"FirstNonNaPosition"=c(1,2,3,3,4,4,4,4,4)
) %>%
  mutate(First_Non_NA_Pos = apply(., 1, function(x) which(!is.na(x))[1]))

   X1 X2   X3 X4 FirstNonNaPosition First_Non_NA_Pos
1 100 NA   NA NA                  1                1
2  NA 10   NA NA                  2                2
3  NA NA 1000 NA                  3                3
4  NA NA 1000 NA                  3                3
5  NA NA   NA 25                  4                4
6  NA NA   NA 50                  4                4
7  NA NA   NA 10                  4                4
8  NA NA   NA 40                  4                4
9  NA NA   NA 50                  4                4

dplyr：需要帮助返回每行中第一个非NA值的列索引

3 个答案:

数据