R重新排列数据框:一些行到列 [英] R re-arrange dataframe: some rows to columns

问题描述

我什至不知道如何正确地为问题命名！

I'm not even sure how to title the question properly!

假设我有一个数据框 d:

Suppose I have a dataframe d:

当前数据框:

d <- data.frame(sample = LETTERS[1:2], cat = letters[11:20], count = c(1:10))

   sample cat count
1       A   k     1
2       B   l     2
3       A   m     3
4       B   n     4
5       A   o     5
6       B   p     6
7       A   q     7
8       B   r     8
9       A   s     9
10      B   t    10

并且我正在尝试重新排列事物，使每个 cat 值成为它自己的一列，sample 仍然是一列(或成为行名称)，而 count 将是新 cat 列中的值，其中0，其中样本没有猫的数量.像这样:

and I'm trying to re-arrange things such that each cat value becomes a column of its own, sample remains a column (or becomes the row name), and count will be the values in the new cat columns, with 0 where a sample doesn't have a count for a cat. Like so:

所需的数据框布局:

   sample   k   l   m   n   o   p   q   r   s   t
1       A   1   0   3   0   5   0   7   0   9   0
2       B   0   2   0   4   0   6   0   8   0  10

解决这个问题的最佳方法是什么?

What's the best way to go about this?

这是我得到的:

for (i in unique(d$sample)) {
    s <- d[d$sample==i,]
    st <- as.data.frame(t(s[,3]))
    colnames(st) <- s$cat
    rownames(st) <- i
} 

即循环遍历原始数据帧中的样本，并对每个样本子集进行转置.所以在这种情况下我得到

i.e. looping through the samples in the original data frame, and transposing for each sample subset. So in this case I get

   k m o q s
 A 1 3 5 7 9

和

   l n p r  t
 B 2 4 6 8 10

这就是我卡住的地方.我用 merge、bind、apply 尝试了很多东西，但我似乎无法正确命中事物.另外，我不禁想知道上面的循环是否是一个必要的步骤——也许是unstack?

And this is where I get stuck. I've tried a bunch of things with merge, bind, apply,... but I can't seem to hit on the right thing. Plus, I can't help but wonder if that loop above is a necessary step at all - something with unstack perhaps?

不用说，我是 R 的新手...如果有人能帮助我，将不胜感激！

Needless to say, I'm new to R... If someone can help me out, it would be greatly appreciated!

PS 原因我试图重新排列我的数据框是为了让绘制值更容易(即我想以表格格式在图中显示实际的 df).

PS Reason I'm trying to re-arrange my dataframe is in the hopes of making plotting of the values easier (i.e. I want to show the actual df in a plot in table format).

谢谢！

推荐答案

Using reshape from base R:

Using reshape from base R:

nn<-reshape(d,timevar="cat",idvar="sample",direction="wide")
names(nn)[-1]<-as.character(d$cat)
nn[is.na(nn)]<-0
> nn
  sample k l m n o p q r s  t
1      A 1 0 3 0 5 0 7 0 9  0
2      B 0 2 0 4 0 6 0 8 0 10

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