在dplyr行总和中忽略NA [英] ignore NA in dplyr row sum
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问题描述
数据< p>是否有一个优雅的方法来处理NA为0(na.rm = TRUE)在dplyr? - data.frame(a = c(1,2,3,4),b = c(4,NA,5,6),c = c(7,8,9,NA))
data%>%mutate(sum = a + b + c)
abc sum
1 4 7 12
2 NA 8 NA
3 5 9 17
4 6 NA NA
但我喜欢得到
abc sum
1 4 7 12
2 NA 8 10
3 5 9 17
4 6 NA 10
即使我知道这不是
解决方案
您可以使用以下内容:
library(dplyr)
data%>%
#rowwise将确保在每行上执行sum操作
rowwise()%> %
#then一个简单的sum(...,na.rm = TRUE)足以导致你需要的
mutate(sum = sum(a,b,c,na.rm = TRUE ))
输出:
资料来源:本地资料框[4 x 4]
群组:< by行>
abc sum
(dbl)(dbl)(dbl)(dbl)
1 1 4 7 12
2 2 NA 8 10
3 3 5 9 17
4 4 6 NA 10
is there an elegant way to handle NA as 0 (na.rm = TRUE) in dplyr?
data <- data.frame(a=c(1,2,3,4), b=c(4,NA,5,6), c=c(7,8,9,NA))
data %>% mutate(sum = a + b + c)
a b c sum
1 4 7 12
2 NA 8 NA
3 5 9 17
4 6 NA NA
but I like to get
a b c sum
1 4 7 12
2 NA 8 10
3 5 9 17
4 6 NA 10
even if I know that this is not the desired result in many other cases
解决方案
You could use this:
library(dplyr)
data %>%
#rowwise will make sure the sum operation will occur on each row
rowwise() %>%
#then a simple sum(..., na.rm=TRUE) is enough to result in what you need
mutate(sum = sum(a,b,c, na.rm=TRUE))
Output:
Source: local data frame [4 x 4]
Groups: <by row>
a b c sum
(dbl) (dbl) (dbl) (dbl)
1 1 4 7 12
2 2 NA 8 10
3 3 5 9 17
4 4 6 NA 10
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