当选择列时,我得到一列我没有选择,但它是一个group_by列:
When selecting columns I get one column I haven't selected but it's a group_by column:
library(magrittr) library(dplyr) df <- data.frame(i=c(1,1,1,1,2,2,2,2), j=c(1,2,1,2,1,2,1,2), x=runif(8)) df %>% group_by(i,j) %>% summarize(s=sum(x)) %>% filter(i==1) %>% select(s)我得到列,即使我没有选择它:
I get column i even I haven't selected it:
i s 1 1 0.8355195 2 1 0.9322474为什么这发生了(为什么不列j?),我该如何避免呢?好的,我可以在开始时过滤....
Why does this happen (why not column j?) and how can I avoid it? Okay I could filter at the beginning....
推荐答案这是因为默认情况下继承了分组变量。请参阅 dplyr 小插曲:
That's because the grouping variable is carried on by default. Please see the dplyr vignette:
分组影响动词如下:分组 select()与未分组的 select()相同,但分组变量始终保留。
Grouping affects the verbs as follows: grouped select() is the same as ungrouped select(), except that grouping variables are always retained.
请注意(每个)总结剥离一层分组(在您的情况下, j ) ,所以在总结之后,您的数据仅按 i 分组,并将其输出到输出中。如果您不想要,可以在选择 s 之前取消分组数据:
Note that (each) summarize peels off one layer of grouping (in your case, j), so after the summarize, your data is only grouped by i and that is printed in the output. If you don't want that, you can ungroup the data before selecting s:
require(dplyr) df %>% group_by(i,j) %>% summarize(s=sum(x)) %>% ungroup() %>% filter(i==1) %>% select(s) #Source: local data frame [2 x 1] # # s #1 1.129867 #2 1.265131更多推荐
dplyr:即使没有选择它,也可以获取group
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