我有一个数据框：
df<-data.frame(Name=c('H001', 'H002', 'H003', 'H004', 'H005', 'H006',
'H007', 'H008', 'H009', 'H0010'),
Room1=rnorm(10,0.4,0.5),
Room2=rnorm(10,0.3,0.5),
Room3=rnorm(10,0.7,0.5),
Weight=sample(1:20,10))
我使用以下方法将Name的每个值乘以其加权因子（Weight）：
weighted_df <- data.frame(df[rep(seq_len(dim(df)[1]), df$Weight), c(1,2,3,4), drop = FALSE], row.names=NULL)
但我想添加第5列ID，以便可以使用唯一的名称和ID组合来标识每一行。产生的df应该看起来像；
name Room1 Room2 Room3 ID
1 H001 0.4390566 0.7158113 0.7400785 1
2 H001 0.4390566 0.7158113 0.7400785 2
3 H001 0.4390566 0.7158113 0.7400785 3
4 H001 0.4390566 0.7158113 0.7400785 4
5 H001 0.4390566 0.7158113 0.7400785 5
6 H001 0.4390566 0.7158113 0.7400785 6
7 H001 0.4390566 0.7158113 0.7400785 7
8 H001 0.4390566 0.7158113 0.7400785 8
9 H001 0.4390566 0.7158113 0.7400785 9
10 H001 0.4390566 0.7158113 0.7400785 10
11 H001 0.4390566 0.7158113 0.7400785 11
12 H001 0.4390566 0.7158113 0.7400785 12
13 H001 0.4390566 0.7158113 0.7400785 13
14 H001 0.4390566 0.7158113 0.7400785 14
15 H001 0.4390566 0.7158113 0.7400785 15
16 H001 0.4390566 0.7158113 0.7400785 16
17 H001 0.4390566 0.7158113 0.7400785 17
18 H002 0.4041108 -0.1668988 0.6594539 1
19 H002 0.4041108 -0.1668988 0.6594539 2
20 H002 0.4041108 -0.1668988 0.6594539 3
提前致谢。
可以使用 rowid
library(data.table)
library(dplyr)
weighted_df %>%
mutate(ID = rowid(Name))
-输出
# Name Room1 Room2 Room3 ID
#1 H001 0.579649851 0.84602529 0.620850211 1
#2 H001 0.579649851 0.84602529 0.620850211 2
#3 H001 0.579649851 0.84602529 0.620850211 3
#4 H001 0.579649851 0.84602529 0.620850211 4
#5 H001 0.579649851 0.84602529 0.620850211 5
#6 H001 0.579649851 0.84602529 0.620850211 6
#7 H001 0.579649851 0.84602529 0.620850211 7
#8 H001 0.579649851 0.84602529 0.620850211 8
#9 H001 0.579649851 0.84602529 0.620850211 9
#10 H001 0.579649851 0.84602529 0.620850211 10
#11 H001 0.579649851 0.84602529 0.620850211 11
#12 H001 0.579649851 0.84602529 0.620850211 12
#13 H001 0.579649851 0.84602529 0.620850211 13
#14 H001 0.579649851 0.84602529 0.620850211 14
#15 H001 0.579649851 0.84602529 0.620850211 15
#16 H001 0.579649851 0.84602529 0.620850211 16
#17 H001 0.579649851 0.84602529 0.620850211 17
#18 H002 1.457267473 -1.18612874 0.553957293 1
#19 H002 1.457267473 -1.18612874 0.553957293 2
# ...
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