问题描述
我有一个名为 ..csv 的文件名，我想为每个测试制作图表.我能看到的最好的方法是为每个 TestName 创建一个 R 表.每个测试产生相同的数据列，所以我想将每个测试的所有数据拉入一个 R 数据表，并为输入数据增加一列.
I have filenames named <InputData>.<TestName>.csv and I'd like to make graphs for each test. The best way I can see to do this is to make one R table for each TestName. Each test produces the same columns of data, so I'd like to pull in all the data for each test into an R datatable with an extra column for the inputdata.
我想做:
read.tables(c("B217.SE.csv", "C10.SE.csv"), sep=",")
产生(例如):
Filename col1 col2
1 B217.SE.csv 1 2
2 B217.SE.csv 2 4
3 C10.SE.csv 3 1
4 C10.SE.csv 4 5
这样做的正确方法是什么?一些我不知道的现有功能?使用 for 循环用 R 语言写出来?
What's the right way to do this? Some existing function I don't know about? Writing it out in the R language using a for loop?
推荐答案
我无法在您的数据上测试它，但您会想要使用 apply 类型的函数，如下所示:
I can't test it on your data, but you will want to use an apply type function like this:
data <- do.call("rbind", lapply(c("file1", "file2"), function(fn)
data.frame(Filename=fn, read.csv(fn)
))
或者，您可以使用 plyr 来简化它.下面是对如何工作的粗略模拟(使用数据框而不是文件):
Or, you can simplify it by using plyr. Here's a rough simulation of how that would work (using data frames instead of files):
> df1 <- data.frame(c1=1:5, c2=rnorm(5))
> df2 <- data.frame(c1=3:7, c2=rnorm(5))
在这种情况下，我将使用 get 而不是 read.csv:
In this case I will use get instead of read.csv:
> data <- ldply(c("df1", "df2"), function(dn) data.frame(Filename=dn, get(dn)))
> data
Filename c1 c2
1 df1 1 -0.15679732
2 df1 2 -0.19392102
3 df1 3 0.01369413
4 df1 4 -0.73942829
5 df1 5 -1.27522427
6 df2 3 -0.33944114
7 df2 4 -0.12509065
8 df2 5 0.11225053
9 df2 6 0.88460684
10 df2 7 -0.70710520
编辑
根据 Marek 的建议，您可以覆盖或创建自己的函数:
Taking Marek's suggestion, you can either overwrite or create your own function:
read.tables <- function(file.names, ...) {
require(plyr)
ldply(file.names, function(fn) data.frame(Filename=fn, read.csv(fn, ...)))
}
data <- read.tables(c("filename1.csv", "filename2.csv"))
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