R dpylr select_if 具有多个条件 [英] R dpylr select_if with multiple conditions

问题描述

我想按名称选择所有数字变量以及一些变量.我设法使用 select_if 来获取数字变量并选择按名称获取变量，但无法将两者合并为一个语句

I would like to select all numeric variables as well as some variables by name. I have managed to use select_if to get the numeric variables and select to get the ones by name but can't combine the two into one statement

x = data.table(c(1,2,3),c(10,11,12),c('a','b','c'),c('x','y','z'), c('l', 'm','n'))

我希望我的结果是:

V1 V2 V4 V5
1 10  x l
2 11  y m
3 12  z n

我试过了，但没有用

y = x %>%
select_if(is.numeric, V4, V5)

推荐答案

如果我们有一个数据框，x:

If we have a data frame, x:

x = data.frame(V1=c(1,2,3),V2=c(10,11,12),V3=c('a','b','c'),V4=c('x','y','z'),V5=c('l', 'm','n'), stringsAsFactors=FALSE)
##  V1 V2 V3 V4 V5
##1  1 10  a  x  l
##2  2 11  b  y  m
##3  3 12  c  z  n

其中 V1 和 V2 实际上是 numeric 而其余的列不是因子，那么我们可以这样做:

where V1 and V2 are actually numeric and the rest of the columns are not factors, then we can do:

library(dplyr)
y <- x %>% select_if(function(col) is.numeric(col) | 
                                   all(col == .$V4) | 
                                   all(col == .$V5))
##  V1 V2 V4 V5
##1  1 10  x  l
##2  2 11  y  m
##3  3 12  z  n

并不是说这是最好的做法，但它确实可以满足您的需求.这里的问题是 select_if 期望它的函数返回一个对应于所有列的布尔向量.

Not saying that this is the best thing to do, but it does do what you want. The issue here is that select_if expects its function to return a boolean vector corresponding to all columns.

另一种方法是使用select:

y <- x %>% select(which(sapply(.,class)=="numeric"),V4,V5)
##  V1 V2 V4 V5
##1  1 10  x  l
##2  2 11  y  m
##3  3 12  z  n

哪个可能更好.

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