[英]How to use mutate from dplyr to create a series of columns defined and called by a vector specifying values for mutation?
I would like to take a column "mpg" from the mtcars dataset and divide each value of it by numbers from 1 to 100. This would create 100 new columns (one column per devisor).我想从 mtcars 数据集中取出一列“mpg”,并将它的每个值除以 1 到 100 之间的数字。这将创建 100 个新列(每个除数一列)。 The names of the columns should be "mpg_div_by_1", "mpg_div_by_2", "mpg_div_by_3".
列的名称应为“mpg_div_by_1”、“mpg_div_by_2”、“mpg_div_by_3”。 I think I read somewhere that dplyr 1.0 could do it in a straightforward way so I dont have to write a loop.
我想我在某处读到 dplyr 1.0 可以以一种简单的方式做到这一点,所以我不必编写循环。
We could use map
variants here.我们可以在这里使用
map
变体。
library(purrr)
library(dplyr)
cols <- 1:5
map_dfc(cols, ~mtcars %>% transmute(!!paste0("mpg_div_by_", .x) := mpg / .x))
# mpg_div_by_1 mpg_div_by_2 mpg_div_by_3 mpg_div_by_4 mpg_div_by_5
#1 21.0 10.50 7.000000 5.250 4.20
#2 21.0 10.50 7.000000 5.250 4.20
#3 22.8 11.40 7.600000 5.700 4.56
#4 21.4 10.70 7.133333 5.350 4.28
#5 18.7 9.35 6.233333 4.675 3.74
#....
To add it to original dataframes we can use bind_cols
:要将其添加到原始数据帧中,我们可以使用
bind_cols
:
map_dfc(cols, ~mtcars %>% transmute(!!paste0("mpg_div_by_", .x) := mpg / .x)) %>%
bind_cols(mtcars, .)
This is much simpler in base R:这在基础 R 中要简单得多:
mtcars[paste0("mpg_div_by_", cols)] <- lapply(cols, function(x) mtcars$mpg / x)
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