Question

我有以下data.frame

df = structure(list(HEADER = c("HOME_TRPM", "AWAY_TRPM", "HOME_TEAM","AWAY_TEAM"),
                     price = c("0.863104076023855", "-0.845186446996287","CHA", "NOP")),
               .Names = c("HEADER", "price"), row.names = c(NA, 4L), class = "data.frame")

df
#>      HEADER              price
#> 1 HOME_TRPM  0.863104076023855
#> 2 AWAY_TRPM -0.845186446996287
#> 3 HOME_TEAM                CHA
#> 4 AWAY_TEAM                NOP

我要转置。如何在不使用t（）的情况下在dplyr中执行此操作？我试过了

df %>% tidyr::spread(HEADER , price)

但它没有给出扁平结构，而是这样做：

structure(list(AWAY_TEAM = c(NA, NA, NA, "NOP"),
     AWAY_TRPM = c(NA, "-0.845186446996287", NA, NA), 
     HOME_TEAM = c(NA, NA, "CHA", NA),
     HOME_TRPM = c("0.863104076023855", NA, NA, NA)),
 .Names = c("AWAY_TEAM", "AWAY_TRPM", "HOME_TEAM", "HOME_TRPM"),
 class = "data.frame", row.names = c(NA, 4L))

生成的data.frame应该是这样的：

structure(list(HOME_TRPM = "0.863104076023855",
    AWAY_TRPM = "-0.845186446996287",
    HOME_TEAM = "CHA", 
    AWAY_TEAM = "NOP"), 
.Names = c("HOME_TRPM", "AWAY_TRPM", "HOME_TEAM", "AWAY_TEAM"), 
row.names = c(NA, -1L), class = "data.frame"))

Answer 1

我认为您需要tidyr而不是dplyr：

library(tidyr)
library(dplyr)
df %>% mutate(group = 1) %>%
       spread(HEADER, price)

  group AWAY_TEAM          AWAY_TRPM HOME_TEAM         HOME_TRPM
1     1       NOP -0.845186446996287       CHA 0.863104076023855

使用此功能，您可以指定分组 - 然后您可以添加select(-group)以便稍后将其删除。

Answer 2

spread已退休，tidyr现在建议使用pivot_wide()：

library(tidyverse)
df %>%
    pivot_wider(names_from = HEADER, values_from = price)

Answer 3

使用tibble系列的tidyverse软件包，可以消除t()的不良影响。

 df_t = as_tibble(t(df), rownames = "row_names")

Answer 4

自从最初发布以来，他们一定已经更新了提迪尔，因为我认为它确实满足了您最初的要求：

> library(dplyr)
> library(tidyr)
Warning message:
package ‘tidyr’ was built under R version 3.4.4 
> df
         HEADER              price
    1 HOME_TRPM  0.863104076023855
    2 AWAY_TRPM -0.845186446996287
    3 HOME_TEAM                CHA
    4 AWAY_TEAM                NOP

    > tidyr::spread(df, HEADER, price)
      AWAY_TEAM          AWAY_TRPM HOME_TEAM         HOME_TRPM
    1       NOP -0.845186446996287       CHA 0.863104076023855

如果您有更大的数据框，则可以随时收集然后传播：

> mdf <- data.frame(Things = c("Cookies","Cake","Knives","Kittens", "Politics"), Darkness = sample(1:5), Despair = sample(1:5), Defeat = sample(1:5))> mdf 
    Things Darkness Despair Defeat
1  Cookies        3       4      1
2     Cake        2       2      5
3   Knives        1       3      2
4  Kittens        5       5      3
5 Politics        4       1      4
> mdf %>% tidyr::gather(Idea, Warning_Level, Darkness:Defeat)
     Things     Idea Warning_Level
1   Cookies Darkness             3
2      Cake Darkness             2
3    Knives Darkness             1
4   Kittens Darkness             5
5  Politics Darkness             4
6   Cookies  Despair             4
7      Cake  Despair             2
8    Knives  Despair             3
9   Kittens  Despair             5
10 Politics  Despair             1
11  Cookies   Defeat             1
12     Cake   Defeat             5
13   Knives   Defeat             2
14  Kittens   Defeat             3
15 Politics   Defeat             4
> mdf %>% tidyr::gather(Idea, Warning_Level, Darkness:Defeat) %>% tidyr::spread(Things, Warning_Level)
      Idea Cake Cookies Kittens Knives Politics
1 Darkness    2       3       5      1        4
2   Defeat    5       1       3      2        4
3  Despair    2       4       5      3        1

在dplyr中转置

4 个答案: