[英]How to use dplyr to return the grouped sum of all numeric columns when there are NA values?
I'm was attempting to sum all numeric columns using dplyr's group_by and summarise functions as below.我正在尝试使用 dplyr 的 group_by 对所有数字列求和,并汇总如下函数。 I didn't understand the error returned from the summarise function and cannot seem to find a similar example on stack overflow ... however after two members pointed out my error in making the example data I found that the code I had to prepared to provide a grouped summary sum report was correct!
我不明白 summarise 函数返回的错误,并且似乎找不到堆栈溢出的类似示例......但是在两个成员指出我在制作示例数据时出错后,我发现我必须准备提供的代码分组汇总总和报告是正确的!
# Dummy data
a <- c(1, NA, 1, NA, 1, 1)
b <- c( NA, 1, NA, 1, NA, NA)
c <- c( 1, 1, 1, NA, 1, 1)
d <- c( 1, 1, 1, NA, 1, NA)
e <- c( NA, 1, 1, NA, 1, 1)
f <- c( 1, NA, 1, NA, 1, 1)
# Make a tibble
tmp <- bind_cols(a, b, c, d, e)
names(tmp) <- c("A", "B", "C", "D", "E")
ID <- c("X", "X", "Y", "Y", "Z", "Z")
tmp <-bind_cols(ID, tmp)
names(tmp)[1] <- "ID"
# Return a sum report
tmp %>%
group_by(ID) %>%
summarise(across(everything(), ~ sum(.x, na.rm = TRUE)))
# A tibble: 3 × 6
ID A B C D E
<chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 X 1 1 2 2 1
2 Y 1 1 1 1 1
3 Z 2 0 2 1 2
It's best to avoid defining a vector with different data types because R will convert the vector to a single data type.最好避免定义具有不同数据类型的向量,因为 R 会将向量转换为单一数据类型。
I think you might want to create your data like this:我认为您可能希望像这样创建数据:
tmp = tibble(
ID = c('X', 'X', 'Y', 'Y', 'Z', 'Z'),
A = c(1, NA, 1, 1, NA, 1),
B = c(NA, 1, 1, 1, 1, NA),
C = c(1, NA, 1, 1, 1, 1),
D = c(NA, 1, NA, NA, NA, NA),
E = c(1, NA, 1, 1, 1, 1))
And then do:然后做:
tmp %>%
group_by(ID) %>%
summarise(across(everything(), ~ sum(.x, na.rm = TRUE)))
To get:要得到:
# A tibble: 3 x 6
ID A B C D E
<chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 X 1 1 1 1 1
2 Y 2 2 2 0 2
3 Z 1 1 2 0 2
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