89

我怎样才能使用管道操作符来管道到替换功能colnames()<-呢？

这是我正在尝试做的事情：

library(dplyr)
averages_df <- 
   group_by(mtcars, cyl) %>%
   summarise(mean(disp), mean(hp))
colnames(averages_df) <- c("cyl", "disp_mean", "hp_mean")
averages_df

# Source: local data frame [3 x 3]
# 
#   cyl disp_mean   hp_mean
# 1   4  105.1364  82.63636
# 2   6  183.3143 122.28571
# 3   8  353.1000 209.21429

但理想情况下，它会是这样的：

averages_df <- 
  group_by(mtcars, cyl) %>%
  summarise(mean(disp), mean(hp)) %>%
  add_colnames(c("cyl", "disp_mean", "hp_mean"))

有没有办法做到这一点，而无需每次都编写专业函数？

这里的答案是一个开始，但不完全是我的问题：Chaining算术运算符 in dplyr

4

3 回答 3

126

您可以使用colnames<-或setNames（感谢@David Arenburg）

group_by(mtcars, cyl) %>%
  summarise(mean(disp), mean(hp)) %>%
  `colnames<-`(c("cyl", "disp_mean", "hp_mean"))
  # or
  # `names<-`(c("cyl", "disp_mean", "hp_mean"))
  # setNames(., c("cyl", "disp_mean", "hp_mean")) 

#   cyl disp_mean   hp_mean
# 1   4  105.1364  82.63636
# 2   6  183.3143 122.28571
# 3   8  353.1000 209.21429

或从 中选择一个Alias( set_colnames) magrittr：

library(magrittr)
group_by(mtcars, cyl) %>%
  summarise(mean(disp), mean(hp)) %>%
  set_colnames(c("cyl", "disp_mean", "hp_mean"))

dplyr::rename如果您只是（重新）命名许多列中的几个可能会更方便（它需要同时编写旧名称和新名称；请参阅@Richard Scriven 的回答）

于 2015-01-23T00:04:01.403 回答
25

在dplyr中，有几种不同的方法可以重命名列。

一是使用rename()功能。在此示例中，您需要对由 创建的名称进行反引号summarise()，因为它们是表达式。 

group_by(mtcars, cyl) %>%
    summarise(mean(disp), mean(hp)) %>%
    rename(disp_mean = `mean(disp)`, hp_mean = `mean(hp)`)
#   cyl disp_mean   hp_mean
# 1   4  105.1364  82.63636
# 2   6  183.3143 122.28571
# 3   8  353.1000 209.21429

你也可以使用select(). 这更容易一些，因为我们可以使用列号，而无需弄乱反引号。

group_by(mtcars, cyl) %>%
    summarise(mean(disp), mean(hp)) %>%
    select(1, disp_mean = 2, hp_mean = 3)

但是对于此示例，最好的方法是执行 @thelatemail 在评论中提到的操作，即返回一步并将列命名为summarise().

group_by(mtcars, cyl) %>%
    summarise(disp_mean = mean(disp), hp_mean = mean(hp))
于 2015-01-23T00:11:14.627 回答
13

我们可以使用带有 dplyr 的.funs参数为汇总变量添加后缀summarise_at，如下代码所示。

library(dplyr)

# summarise_at with dplyr
mtcars %>% 
  group_by(cyl) %>%
  summarise_at(
    .cols = c("disp", "hp"),
    .funs = c(mean="mean")
  )
# A tibble: 3 × 3
# cyl disp_mean   hp_mean
# <dbl>     <dbl>     <dbl>
# 1     4  105.1364  82.63636
# 2     6  183.3143 122.28571
# 3     8  353.1000 209.21429

此外，我们可以通过多种方式设置列名。

# set_names with magrittr
mtcars %>% 
  group_by(cyl) %>%
  summarise(mean(disp), mean(hp)) %>%
  magrittr::set_names(c("cyl", "disp_mean", "hp_mean"))

# set_names with purrr
mtcars %>% 
  group_by(cyl) %>%
  summarise(mean(disp), mean(hp)) %>%
  purrr::set_names(c("cyl", "disp_mean", "hp_mean"))

# setNames with stats
mtcars %>%
  group_by(cyl) %>%
  summarise(mean(disp), mean(hp)) %>%
  stats::setNames(c("cyl", "disp_mean", "hp_mean"))

# A tibble: 3 × 3
# cyl disp_mean   hp_mean
# <dbl>     <dbl>     <dbl>
# 1     4  105.1364  82.63636
# 2     6  183.3143 122.28571
# 3     8  353.1000 209.21429
于 2017-01-26T03:58:56.173 回答