r-为特定列中的每个变量拆分并创建一个新的数据帧

Question

我不确定如何在这个问题上取得进展。我在这里使用这个mtcars数据集：

structure(list(index = 1:32, car = c("Mazda RX4", "Mazda RX4 Wag", 
"Datsun 710", "Hornet 4 Drive", "Hornet Sportabout", "Valiant", 
"Duster 360", "Merc 240D", "Merc 230", "Merc 280", "Merc 280C", 
"Merc 450SE", "Merc 450SL", "Merc 450SLC", "Cadillac Fleetwood", 
"Lincoln Continental", "Chrysler Imperial", "Fiat 128", "Honda Civic", 
"Toyota Corolla", "Toyota Corona", "Dodge Challenger", "AMC Javelin", 
"Camaro Z28", "Pontiac Firebird", "Fiat X1-9", "Porsche 914-2", 
"Lotus Europa", "Ford Pantera L", "Ferrari Dino", "Maserati Bora", 
"Volvo 142E"), mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1, 14.3, 
24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4, 
30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8, 
19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 
8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8, 4), 
disp = c(160, 160, 108, 258, 360, 225, 360, 146.7, 140.8, 
167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7, 
71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145, 
301, 121), hp = c(110, 110, 93, 110, 175, 105, 245, 62, 95, 
123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150, 
150, 245, 175, 66, 91, 113, 264, 175, 335, 109), drat = c(3.9, 
3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92, 
3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76, 
3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11
), wt = c(2.62, 2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19, 
3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2, 
1.615, 1.835, 2.465, 3.52, 3.435, 3.84, 3.845, 1.935, 2.14, 
1.513, 3.17, 2.77, 3.57, 2.78), qsec = c(16.46, 17.02, 18.61, 
19.44, 17.02, 20.22, 15.84, 20, 22.9, 18.3, 18.9, 17.4, 17.6, 
18, 17.98, 17.82, 17.42, 19.47, 18.52, 19.9, 20.01, 16.87, 
17.3, 15.41, 17.05, 18.9, 16.7, 16.9, 14.5, 15.5, 14.6, 18.6
), vs = c(0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 
0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1), am = c(1, 
1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1), gear = c(4, 4, 4, 3, 
3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3, 
3, 3, 4, 5, 5, 5, 5, 5, 4), carb = c(4, 4, 1, 1, 2, 1, 4, 
2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1, 
2, 2, 4, 6, 8, 2)), row.names = c(NA, -32L), class = c("tbl_df", 
"tbl", "data.frame"))

这是我写的伪代码。

for (i in 1:length(car)) {
mtcars %>%
filter(car == car[i]) %>%
mtcars_i <- mtcars
}

这里的想法是，我想创建32个不同的数据集，在这个特定数据集的标签中包含每辆车的名称。

mtcars_mazda_rx4
mtcars_hornet_sportabout
etc.

这里mtcars_mazda_rx4将是具有所有相同变量但只有一个观测值的数据帧，其中car == "Mazda RX4"，即mtcars[car == "Mazda RX4",]

有没有一种方法可以创建一个for循环，通过特定的变量过滤数据帧，然后输出一个新的数据帧，该数据帧的变量名在新的df中标识？

Answer 1

我们可以使用assign

for (i in 1:length(car)) {
tmp <- mtcars %>%
filter(car == car[i])
assign(paste0('mtcars_', car[i]), tmp)
}

Answer 2

使用split只是一种不同的方法；我使用dplyr使解决方案更加清晰；

library(tidyverse)
mtcars %>% 
#  rownames_to_column("car") %>% ## run this line if you are using original mtcars
split(., .$car) %>% 
set_names(., nm = paste0("mtcars_", names(.))) %>% 
list2env(., envir=.GlobalEnv)