长到宽重组通过ID和天

Question

考虑：

x <- data.frame(Participant=c("1","1","1","1","1","1","1","1","1","1", "2","2","2","2","2","2","2","2","2","2", 
           "3","3","3","3","3","3","3","3","3","3"), 
       Day= c("1","2","3","4","5","6","7","8","9","10","1","2","3","4","5","6","7","8","9","10", 
         "1","2","3","4","5","6","7","8","9","10"), 
       verbal=c(1,4,5,6,1,2,8,5,3,4,1,4,5,6,1,2,8,5,3,4,1,4,5,6,1,2,8,5,3,4), 
       spatial=c(1,6,7,3,5,1,6,7,3,5,1,6,7,3,5,1,6,7,3,5,1,6,7,3,5,1,6,7,3,5), 
       cognitive=c(5,6,3,5,7,1,2,3,6,1,6,7,3,5,1,6,7,3,5,1,6,7,3,5,7,4,2,5,7,4)) 

结果：

y <- data.frame(Participant=c("1","2","3"), 
       verbal1=c(1,4,5), 
       verbal2=c(1,4,5), 
       verbal3=c(1,4,5), 
       verbal4=c(1,4,5), 
       verbal5=c(1,4,5), 
       verbal6=c(1,4,5), 
       verbal7=c(1,4,5), 
       verbal8=c(1,4,5), 
       verbal9=c(1,4,5), 
       verbal10=c(1,4,5), 
       spatial1=c(1,6,7), 
       spatial2=c(1,6,7), 
       spatial3=c(1,6,7), 
       spatial4=c(1,6,7), 
       spatial5=c(1,6,7), 
       spatial6=c(1,6,7), 
       spatial7=c(1,6,7), 
       spatial8=c(1,6,7), 
       spatial9=c(1,6,7), 
       spatial10=c(1,6,7), 
       cognitive1=c(5,6,3), 
       cognitive2=c(5,6,3), 
       cognitive3=c(5,6,3), 
       cognitive4=c(5,6,3), 
       cognitive5=c(5,6,3), 
       cognitive6=c(5,6,3), 
       cognitive7=c(5,6,3), 
       cognitive8=c(5,6,3), 
       cognitive9=c(5,6,3), 
       cognitive10=c(5,6,3)) 

基本上，我有麻烦重组长格式的数据集，以宽格式。这里的问题是需要调用多个变量（口头的，空间的和认知的），所以我不能用TidyR传播函数来打它。这里的关键是要打破它分成三块在评论部分中找到：

解决方案：

x1 <- x %>% 
    select(ParticipantID, Day, verbal) %>% 
    mutate(Day=paste0('verbal', Day)) %>% 
    spread(Day, verbal) 


x2 <- x %>% 
    select(ParticipantID, Day, spatial) %>% 
    mutate(Day=paste0('spatial', Day)) %>% 
    spread(Day, spatial) 

x3 <- x %>% 
    select(ParticipantID, Day, cognitive) %>% 
    mutate(Day=paste0('cognitive', Day)) %>% 
    spread(Day, cognitive) 

final1 <- left_join(x1, x2, by=participant) 
final2 <- left_join(x2,final1, by=participant) 

Answer 1

什么分解成组成部分，然后再结合到一起，就像这样：

library(dplyr) 
library(tidyr) 

x1 <- select(x, Participant, Day, verbal) %>% mutate(Day = paste0('verbal',Day)) 
x2 <- select(x, Participant, Day, spatial) %>% mutate(Day = paste0('spatial',Day)) 
x3 <- select(x, Participant, Day, cognitive) %>% mutate(Day = paste0('cognitive',Day)) 

final <- left_join(left_join(spread(x1, Day, verbal), spread(x2, Day, spatial), by = 'Participant'), spread(x3, Day, cognitive), by = 'Participant') 
final 

# Participant verbal1 verbal10 verbal2 verbal3 verbal4 verbal5 verbal6 verbal7 verbal8 verbal9 spatial1 spatial10 spatial2 spatial3 spatial4 spatial5 
# 1   1  1  4  4  5  6  1  2  8  5  3  1   5  6  7  3  5 
# 2   2  1  4  4  5  6  1  2  8  5  3  1   5  6  7  3  5 
# 3   3  1  4  4  5  6  1  2  8  5  3  1   5  6  7  3  5 
# spatial6 spatial7 spatial8 spatial9 cognitive1 cognitive10 cognitive2 cognitive3 cognitive4 cognitive5 cognitive6 cognitive7 cognitive8 cognitive9 
# 1  1  6  7  3   5   1   6   3   5   7   1   2   3   6 
# 2  1  6  7  3   6   1   7   3   5   1   6   7   3   5 
# 3  1  6  7  3   6   4   7   3   5   7   4   2   5   7