如何在R的列中插入文件名[重复]

Question

假设，我有这样的文件

rock=structure(list(x1 = c(0, 0.8, 0.4, 0.3, 0.5, 1, 0.7, 0.6, 0.4, 
0.4, 0.6), x2 = c(0, 1, 0.5, 0.3, 0.5, 0.5, 0.8, 0.3, 0.6, 0.8, 
0.7), x3 = c(0, 0.4, 0.8, 0.4, 0.2, 1, 0.5, 0.8, 0.4, 1, 0.3), 
    x4 = c(0, 0.3, 0.4, 0.4, 0.5, 0.6, 0.8, 0.3, 0.7, 0.6, 0.2
    )), class = "data.frame", row.names = c(NA, -11L))
rave=structure(list(x1 = c(0, 0.8, 0.4, 0.3, 0.5, 1), x2 = c(0, 1, 
0.5, 0.3, 0.5, 0.5), x3 = c(0, 0.4, 0.8, 0.4, 0.2, 1), x4 = c(0, 
0.3, 0.4, 0.4, 0.5, 0.6)), class = "data.frame", row.names = c(NA, 
-6L))
classic=structure(list(x1 = c(0, 0.8), x2 = 0:1, x3 = c(0, 0.4), x4 = c(0, 
0.3)), class = "data.frame", row.names = c(NA, -2L))

当我rbind这些数据集时，如何为每个数据集粘贴原始名称 即我想看到这样的结果。名称为 csv 格式的初始数据。例如

classic=read.csv(path to classic.csv)

   dataset  x1  x2  x3  x4
1  classic 0.0 0.0 0.0 0.0
2  classic 0.8 1.0 0.4 0.3
3     Rave 0.0 0.0 0.0 0.0
4     Rave 0.8 1.0 0.4 0.3
5     Rave 0.4 0.5 0.8 0.4
6     Rave 0.3 0.3 0.4 0.4
7     Rave 0.5 0.5 0.2 0.5
8     rock 0.0 0.0 0.0 0.0
9     rock 0.8 1.0 0.4 0.3
10    rock 0.4 0.5 0.8 0.4
11    rock 0.3 0.3 0.4 0.4
12    rock 0.5 0.5 0.2 0.5
13    rock 1.0 0.5 1.0 0.6
14    rock 0.7 0.8 0.5 0.8
15    rock 0.6 0.3 0.8 0.3
16    rock 0.4 0.6 0.4 0.7
17    rock 0.4 0.8 1.0 0.6
18    rock 0.6 0.7 0.3 0.2

Answer 1

您可以将具有常量名称的列添加到数据集中，然后 rbind 然后把最后一列放到第一个位置

classic['dataset'] = 'classic'
rave['dataset'] = 'rave'
rock['dataset'] = 'rock'
df <- rbind(classic, rave, rock)
df <- df[,c(ncol(df), 1:ncol(df)-1)]

Answer 2

将它们放在一个列表中并使用bind_rows：

library(dplyr)
bind_rows(lst(rock, rave, classic), .id = 'dataset')

#   dataset  x1  x2  x3  x4
#1     rock 0.0 0.0 0.0 0.0
#2     rock 0.8 1.0 0.4 0.3
#3     rock 0.4 0.5 0.8 0.4
#4     rock 0.3 0.3 0.4 0.4
#5     rock 0.5 0.5 0.2 0.5
#6     rock 1.0 0.5 1.0 0.6
#7     rock 0.7 0.8 0.5 0.8
#8     rock 0.6 0.3 0.8 0.3
#9     rock 0.4 0.6 0.4 0.7
#10    rock 0.4 0.8 1.0 0.6
#11    rock 0.6 0.7 0.3 0.2
#12    rave 0.0 0.0 0.0 0.0
#13    rave 0.8 1.0 0.4 0.3
#14    rave 0.4 0.5 0.8 0.4
#15    rave 0.3 0.3 0.4 0.4
#16    rave 0.5 0.5 0.2 0.5
#17    rave 1.0 0.5 1.0 0.6
#18 classic 0.0 0.0 0.0 0.0
#19 classic 0.8 1.0 0.4 0.3

---

但是，如果您可以自动读取列表中的数据而无需先单独读取它们，那会更好。

library(dplyr)
library(purrr)

filenames <- list.files('/path/to/csv', pattern = '\\.csv', full.names = TRUE)

result <- map_df(filenames, 
                 ~read.csv(.x) %>% 
                   mutate(dataset = tools::file_path_sans_ext(basename(.x))))