【问题标题】:How to transform a data frame with identical column names如何转换具有相同列名的数据框
【发布时间】:2020-05-19 16:13:16
【问题描述】:

我有一个像这样的df:

df <- data.frame( name = c("mouse", "rat"), cont = c(27L, 83L), cont = c(43L, 45L), cont = c(18L, 54L), 
treat = c(49040L, 53522L), treat = c(48570L, 22235L), treat = c(138888L, 345667L))

name   cont cont cont treat  treat  treat
mouse   27   43  18   49040  48570  138888
rat     83   45  54   53522  22235  345667 

我在 df 上通过meltData &lt;- melt(df) 执行了melt 函数,但我得到的所有行都相同,我的意思是:

variable value
 cont      27
 cont      83
 cont      27
 cont      83
 treat     49040
 treat     53522  
 treat     49040
 treat     53522
        .
        .
        .

期望的输出应该是:

variable value
 cont      27
 cont      83
 cont      43
 cont      45
 treat     49040
 treat     53522  
 treat     48570
 treat     22235
        .
        .
        .

我尝试了不同的融化方式,但无法弄清楚我错过了什么。任何帮助将不胜感激。

【问题讨论】:

标签: r dataframe reshape melt


【解决方案1】:

您可以改用data.table::melt()

library(data.table)
setDT(df)
melt(df, id.vars = "name")[, variable := sub("\\..+", "", variable)
                           ][, !"name"]

    variable  value
 1:     cont     27
 2:     cont     83
 3:     cont     43
 4:     cont     45
 5:     cont     18
 6:     cont     54
 7:    treat  49040
 8:    treat  53522
 9:    treat  48570
10:    treat  22235
11:    treat 138888
12:    treat 345667

stack() 来自基础 R:

dfl <- stack(df[-1])
dfl$ind <- sub("\\..+", "", dfl$ind)
dfl
   values   ind
1      27  cont
2      83  cont
3      43  cont
4      45  cont
5      18  cont
6      54  cont
7   49040 treat
8   53522 treat
9   48570 treat
10  22235 treat
11 138888 treat
12 345667 treat

数据

df <- data.frame(
  name = c("mouse", "rat"), 
  cont = c(27L, 83L), 
  cont = c(43L, 45L), 
  cont = c(18L, 54L), 
  treat = c(49040L, 53522L), 
  treat = c(48570L, 22235L), 
  treat = c(138888L, 345667L)
)

【讨论】:

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