是否可以在类似于 dcast 的 tidyr 中的多列上使用传播? [英] Is it possible to use spread on multiple columns in tidyr similar to dcast?

问题描述

我有以下虚拟数据:

library(dplyr)
library(tidyr)
library(reshape2)
dt <- expand.grid(Year = 1990:2014, Product=LETTERS[1:8], Country = paste0(LETTERS, "I")) %>%   select(Product, Country, Year)
dt$value <- rnorm(nrow(dt))

我选择了两种产品-国家/地区组合

I pick two product-country combinations

sdt <- dt %>% filter((Product == "A" & Country == "AI") | (Product == "B" & Country =="EI"))

并且我想并排查看每个组合的值.我可以用 dcast 做到这一点:

and I want to see the values side by side for each combination. I can do this with dcast:

sdt %>% dcast(Year ~ Product + Country)

是否可以使用 tidyr 包中的 spread 来做到这一点?

Is it possible to do this with spread from the package tidyr?

推荐答案

一种选择是通过 paste 加入 'Product' 和 'Country' 列来创建一个新的 'Prod_Count'，删除那些带有 select 的列，并使用 tidyr 中的 spread 从long"到wide"重新整形.

One option would be to create a new 'Prod_Count' by joining the 'Product' and 'Country' columns by paste, remove those columns with the select and reshape from 'long' to 'wide' using spread from tidyr.

 library(dplyr)
 library(tidyr)
 sdt %>%
 mutate(Prod_Count=paste(Product, Country, sep="_")) %>%
 select(-Product, -Country)%>% 
 spread(Prod_Count, value)%>%
 head(2)
 #  Year      A_AI       B_EI
 #1 1990 0.7878674  0.2486044
 #2 1991 0.2343285 -1.1694878

或者我们可以通过使用 tidyr(来自@beetroot 的评论)中的 unite 来避免几个步骤并像以前一样重塑.

Or we can avoid a couple of steps by using unite from tidyr (from @beetroot's comment) and reshape as before.

 sdt%>% 
 unite(Prod_Count, Product,Country) %>%
 spread(Prod_Count, value)%>% 
 head(2)
 #   Year      A_AI       B_EI
 # 1 1990 0.7878674  0.2486044
 # 2 1991 0.2343285 -1.1694878

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