用因子列融解R data.table [英] Melting an R data.table with a factor column

问题描述

我有以下R data.table（尽管它也应随data.frame缩放）。目的是重塑此data.table，以在 ggplot2 中作为散点图进行绘制。因此，我需要重塑此data.table，使其具有一个因素列来为这些点着色：

I have the following R data.table (though this should scale with a data.frame too). The goal is to reshape this data.table to plot as a scatterplot in ggplot2. I therefore need to reshape this data.table to have one "factor" column to color the points:

> library(data.table)
> dt
   ID                   x_A               y_A        x_B       y_B                                                                                                                                                                                                  
   1:   05AC            0.81               3          0.92      2.05                                                                                                                                                                                                   
   2:   01BA            0.41               5          0.63      1.8                                                                                                                                                                                                   
   3:   Z1AC            0.41               5          0.58      1.8                                                                                                                                                                                                   
   4:   B2BA            0.21             6.5          1.00      1.8   
   ....

我相信正确的输出格式必须为：

I believe the correct output needs to be of the form:

ID     type   x      y
05AC   A      0.81   3       
05AC   B      0.92   2.05
01BA   A      0.41   5 
01BA   B      0.63   1.8
Z1AC   A      0.41   5 
Z1AC   B      0.58   1.8
B2BA   A      0.21   6.5 
B2BA   B      1.00   1.8

是否有一种标准的方式以这种方式展开 data.table？我很高兴在这种情况下可以使用dplyr，但我怀疑应该有一个data.table方法。

Is there a standard way to "unfold" data.tables in this fashion? I'm happy for how to use dplyr in this case, but I suspect there should be a data.table method.

melt（）可以，如果我能弄清楚如何创建列键入，例如

melt() would work, if I could figure out how to create the column type, e.g.

melt(dt, id.vars=c("ID")) 

只会根据一列 ID

我特别困惑如何分别从2-3列和4-5列中擦除 A和B类型...

I'm especially confused how one "scrapes" the A and B type from columns 2-3 and columns 4-5 respectively...

推荐答案

在建议的使用融化的方法之后，留在 data.table 中，您可以 tstrsplit 来基于 _字符拆分变量。

Staying within data.table, after your suggested approach of using melt, you can tstrsplit to split the variable based on the "_" character.

## use tstrsplit to split a column on a regular expression
dt[, c("xy", "type") := tstrsplit(variable, "_")]
dt 
#       ID variable value xy type
#  1: 05AC      x_A  0.81  x    A
#  2: 01BA      x_A  0.41  x    A
#  3: Z1AC      x_A  0.41  x    A
#  4: B2BA      x_A  0.21  x    A
#  5: 05AC      y_A  3.00  y    A
#  6: 01BA      y_A  5.00  y    A
#  7: Z1AC      y_A  5.00  y    A
#  8: B2BA      y_A  6.50  y    A
#  9: 05AC      x_B  0.92  x    B
# 10: 01BA      x_B  0.63  x    B
# 11: Z1AC      x_B  0.58  x    B
# 12: B2BA      x_B  1.00  x    B
# 13: 05AC      y_B  2.05  y    B
# 14: 01BA      y_B  1.80  y    B
# 15: Z1AC      y_B  1.80  y    B
# 16: B2BA      y_B  1.80  y    B

这为您提供了所需解决方案的详细形式。然后，您可以使用 dcast 扩大它

This gives you the long-form of your required solution. You can then use dcast to widen it

dcast(dt, formula = ID + type ~ xy)

#      ID type    x    y
# 1: 01BA    A 0.41 5.00
# 2: 01BA    B 0.63 1.80
# 3: 05AC    A 0.81 3.00
# 4: 05AC    B 0.92 2.05
# 5: B2BA    A 0.21 6.50
# 6: B2BA    B 1.00 1.80
# 7: Z1AC    A 0.41 5.00
# 8: Z1AC    B 0.58 1.80

此答案的逻辑与建议的 dplyr 方法，将收集％&％;％分开％>％价差，但使用 data.table 。

The logic of this answer is the same as the suggested dplyr approach of gather %>% separate %>% spread, but using data.table.

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