如何列出我的全局环境中的所有数据框？

I am trying to use rbind on them. But I need a list of all the dataframes that are already in my global environment. How can I do it?

我试图在他们身上使用rbind。但是我需要一个已经存在于我的全局环境中的所有数据帧的列表。我该怎么做?

Code I used to import the 20 csv files in a directory. Basically, have to combine into a single dataframe.

代码我用来导入目录中的20个csv文件。基本上,必须组合成一个数据帧。

temp = list.files(pattern = "*.csv")
for (i in 1:length(temp)) assign(temp[i], read.csv(temp[i]))

6 个解决方案

#1

From your posted code, I would recommend you start a new R session, and read the files in again with the following code

从您发布的代码中,我建议您启动一个新的R会话,并使用以下代码再次读取文件

do.call(rbind, lapply(list.files(pattern = ".csv"), read.csv))

#2

This function should return a proper list with all the data.frames as elements

此函数应返回一个包含所有data.frames作为元素的正确列表

dfs <- Filter(function(x) is(x, "data.frame"), mget(ls()))

then you can rbind them with

然后你可以用它们来对抗它们

do.call(rbind, dfs)

Of course it's awfully silly to have a bunch of data.frames lying around that are so related that you want to rbind them. It sounds like they probably should have been in a list in the first place.

当然,拥有一堆数据框架是非常愚蠢的,这些数据框架是如此相关以至于你想要它们。听起来他们可能应该首先列入清单。

I recommend you say away from assign(), that's always a sign things are probably afoul. Try

我建议你远离assign(),这总是一个迹象,事情可能会发生冲突。尝试

temp <- list.files(pattern="*.csv")
dfs <- lapply(temp, read.csv)

that should return a list straight away.

应该立即返回一个列表。

#3

If you only have data.frames with the same number of columns and column names in you global environment, the following should work (non-data.frame object don't matter):

如果您在全局环境中只有具有相同列数和列名的data.frames,则以下内容应该有效(非data.frame对象无关紧要):

do.call(rbind, eapply(.GlobalEnv,function(x) if(is.data.frame(x)) x))

#4

This is a slight improvement on MentatOfDune's answer, which does not catch data.frames with multiple classes:

这是MentatOfDune的答案略有改进,它没有捕获具有多个类的data.frames:

ls()[grepl('data.frame', sapply(ls(), function(x) class(get(x))))]

#5

The ls function lists all things in your environment. The get function gets a variable with a given name. You can use the class function to get the class of a variable.

ls函数列出了环境中的所有内容。 get函数获取具有给定名称的变量。您可以使用类函数来获取变量的类。

If you put them all together, you can do this:

如果你把它们放在一起,你可以这样做:

ls()[sapply(ls(), function(x) class(get(x))) == 'data.frame']

which will return a character vector of the data.frames in the current environment.

这将返回当前环境中data.frames的字符向量。

#6

To improve MentatOfDune's answer (great username by the way):

要改进MentatOfDune的答案(顺便说一句,用户名是:)

ls()[sapply(ls(), function(x) any(class(get(x)) == 'data.frame'))]

This also supports tibbles (created with dplyr for example), because they contain multiple classes, where data.frame is one of them.

这也支持tibbles(例如用dplyr创建),因为它们包含多个类,其中data.frame就是其中之一。

#1