我一直在尝试从具有多个ID和值列的宽格式转换为长格式。我希望将tidyr解决方案作为dcast使用，因为默认设置为length。
这是我到目前为止尝试过的：
df_wide <- df %>%
melt(id.vars = c(Route, Address, Week)) %>%
dcast(Route + Address ~ variable + Week)
数据：
df <- read.table(text = "
Route Week Address V1 V2 V3 V4 V5
A Week1 12345_SE_Court 0 1 0 0 0
A Week2 12345_SE_Court 0 0 1 1 1
B Week1 98765_NW_Drive 1 1 0 0 1
B Week2 98765_NW_Drive 0 1 0 1 0
C Week1 10293_SW_Road 0 0 0 0 1
C Week2 10293_SW_Road 1 0 0 0 1
A Week1 33333_NE_Street 0 1 1 0 0
A Week2 33333_NE_Street 1 0 1 0 0"
, header = TRUE)
所需的输出：
Route Address V1.Week1 V2.Week1 V3.Week1 V4.Week1 V5.Week1 V1.Week1 V2.Week2 V3.Week2 V4.Week2 V5.Week2
A 12345_SE_Court 0 1 0 0 0 0 0 1 1 1
A 33333_NE_Street 0 1 1 0 1 0 1 0 0 0
B 98765_NW_Drive 1 1 0 0 1 0 1 0 1 0
C 10293_SW_Road 0 0 0 0 1 1 0 0 0 1
答案 0 :(得分：2)
这是使用tidyr进行此操作的方法。诀窍是您需要先进行gather：
library(tidyr)
df_wide <- df %>%
gather(key, value, V1:V5) %>%
unite("key", key, Week, sep = ".") %>%
spread(key, value)
df_wide
#> Route Address V1.Week1 V1.Week2 V2.Week1 V2.Week2 V3.Week1
#> 1 A 12345_SE_Court 0 0 1 0 0
#> 2 A 33333_NE_Street 0 1 1 0 1
#> 3 B 98765_NW_Drive 1 0 1 1 0
#> 4 C 10293_SW_Road 0 1 0 0 0
#> V3.Week2 V4.Week1 V4.Week2 V5.Week1 V5.Week2
#> 1 1 0 1 0 1
#> 2 1 0 0 0 0
#> 3 0 0 1 1 0
#> 4 0 0 0 1 1
由reprex package（v0.2.0）于2018-06-27创建。