根据共享值和R中的字符串为数据框分配颜色 [英] Assign colors to a data frame based on shared values with a character string in R

问题描述

我正在R中工作。我有许多不同的数据框，其中都带有样品名称，我正在尝试根据样品名称为每个数据框中的每一行分配一种颜色。其中有许多行具有相同的样品名称，但是我的输出数据比较混乱，因此无法按样品名称进行排序。这是我所拥有的一个小例子

I'm working in R. I have many different data frames that have sample names in them and I'm trying to assign a color to each row in each data frame based on the sample names. There are many rows that have the same sample names in them, but I have messy output data so I can't sort by sample name. Here's a small example case of what I have

names          <- c( "TC3", "102", "172", "136", "142", "143", "AC2G" )
colors         <- c( "darkorange", "forestgreen", "darkolivegreen", "darkgreen", "darksalmon", "firebrick3", "firebrick1" )
dataA          <- c( "JR13-101A", "TC3B", "JR12-136C", "AC2GA", "TC3A" )
newcolors      <- rep( NA, length( dataA ) )
dataA          <- as.data.frame( cbind( dataA, newcolors ) )

并且我尝试了以下操作（我知道有循环，但这就是我想做的全部）。我也想摆脱R循环的困扰，但我还没有改变习惯。

这就是我尝试过的方法。可能很明显，但是对于所有 newcolors

and I've tried the following (with loops, I know, but that's all I could think to do). I'm also trying to get away from falling back on loops in R, but I have yet to break the habit.
Here's what I've tried. Probably something obvious, but I just get NA returned for all the newcolors

for( i in 1:nrow( dataA ) ) {
  for( j in 1:length( names ) ) {
    if( grepl( dataA$dataA[ i ], names[ j ] ) ) {
   dataA$newcolors[ i ]  <- colors[ j ] 
    }
  }
}

推荐答案

这是一个解决方案，它消除了1个循环：

Here is a solution, which eliminates 1 loop:

dataA$newcolors<-as.character(dataA$newcolors)
for( j in 1:length( names ) ) {
    dataA$newcolors[grep(names[j], dataA$dataA)] <- colors[j] 
}

将newcolors列转换为字符而不是因数会使更新变得更加容易。如果名称的数量很短，那么单循环对性能的影响不会很大。

Converting the newcolors column to character instead of a factor makes the updating much easier. If the number of names is short then there should not be much of a performance impact with the single loop.

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