对具有相似名称的列按行求和 [英] Sum columns row-wise with similar names

问题描述

我有一个 dataframe，其中有很多类似这样的列:

I have a dataframe that has lots of columns that are something like this:

data <- data.frame (a.1 = 1:5, a.2b = 3:7, a.5 = 5:9, bt.16 = 4:8, bt.12342 = 7:11)

我想要一个包含对具有相同前缀的变量求和的列的结果.在这个例子中，我想返回一个数据框:a = (9:13), bt = (11:15)

I'd like a result with columns that sum the variables that have the same prefix. In this example, I want to return a dataframe: a = (9:13), bt = (11:15)

我的真实数据集相当复杂(我想结合具有不同 utm 参数的网页的页面查看次数)，但这种情况的解决方案应该让我走上正轨.

My real data set is quite a bit more complicated (I want to combine page view counts for web pages with different utm parameters) but a solution for this case should put me on the right track.

推荐答案

这里有一个基于 R 的解决方案:

Here a solution with base R:

> prefixes = unique(sub("\..*", "", colnames(data)))
> sapply(prefixes, function(x)rowSums(data[,startsWith(colnames(data), x)]))
      a bt
[1,]  9 11
[2,] 12 13
[3,] 15 15
[4,] 18 17
[5,] 21 19

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