在R中的另一个函数中使用ggplot（） [英] Use of ggplot() within another function in R

问题描述

我试图用ggplot2库编写一个简单的绘图函数。考虑一个 data.frame 称为表示存储两个条件和两个我想要绘制的平均值（条件将出现在X轴上，表示在Y上）。 $ b $> b（pre> library（ggplot2）
m <-c（13.8,14.8）
cond <-c（1,2）
表示< ; - data.frame（means = m，condition = cond）
表示
＃输出应该是：
＃表示条件
＃1 13.8 1
＃2 14.8 2

testplot < - function（meansdf）
{
p < - ggplot（meansdf，aes（fill = meansdf $ condition，y = meansdf $ means，x = meansdf $ condition））
p + geom_bar（position =dodge，stat =identity）
}

testplot（means）
＃这将输出以下错误：
＃eval中的错误（expr，envir，enclos）：object'meansdf'not found


所以看起来ggplot正在调用 eval ，它找不到argum ent meansdf 。有没有人知道我可以如何成功地将函数参数传递给ggplot？

（注意：我可以直接调用ggplot函数，但最终我希望因为Joris和Chase已经正确地回答了，标准的最佳实践就是让我们的绘图函数做更复杂的东西！:) 只需简单地省略 meansdf $ 部分并直接引用数据框列即可。

  testplot < -  function（meansdf）
 {
p < -  ggplot（meansdf，
 aes（fill = condition，
y = means，
x = condition） ）
p + geom_bar（position =dodge，stat =identity）
} 
  

$ b $这是可行的，因为在 aes 中引用的变量既可以在全局环境中查找，也可以在传递给 ggplot 。这也是为什么你的示例代码（使用 meansdf $ condition 等）不起作用的原因： meansdf 既不是在全球环境中可用，在传递给 ggplot ，也就是 meansdf 本身的数据框内也不可用。 / p>

---

事实上，在全局环境而不是在调用环境中查找变量实际上是 ggplot2中的一个已知错误，目前Hadley认为不可修复。
如果希望使用局部变量（例如 scale ）来影响用于该图的数据，则会导致问题：

  testplot<  -  function（meansdf）
 {
 scale < -  0.5 
p < -  ggplot（meansdf ，
 aes（fill = condition，
y = means * scale，＃不起作用，因为找不到比例
x = condition））
p + geom_bar（position =dodge ，stat =identity）
} 
  

为这种情况提供了一个非常好的解决方法由Winston Chang引用的GitHub问题：在调用 ggplot 时，显式地将环境参数设置为当前环境。
下面是上面例子的样子：

  testplot<  -  function（meansdf）
 
 scale <-0.5 
p < -  ggplot（meansdf，
 aes（fill = condition，
y = means * scale，
x = condition），
 environment = environment（））＃这是唯一更改/添加的行
p + geom_bar（position =dodge，stat =identity）
} 
 
 ##现在，下面的工作
 testplot（表示）
  

I'm trying to write a simple plot function, using the ggplot2 library. But the call to ggplot doesn't find the function argument.

Consider a data.frame called means that stores two conditions and two mean values that I want to plot (condition will appear on the X axis, means on the Y).

library(ggplot2)
m <- c(13.8, 14.8)
cond <- c(1, 2)
means <- data.frame(means=m, condition=cond)
means
# The output should be:
#     means    condition
#   1 13.8     1
#   2 14.8     2

testplot <- function(meansdf)
{
  p <- ggplot(meansdf, aes(fill=meansdf$condition, y=meansdf$means, x = meansdf$condition))
  p + geom_bar(position="dodge", stat="identity")
}

testplot(means)
# This will output the following error:
# Error in eval(expr, envir, enclos) : object 'meansdf' not found

So it seems that ggplot is calling eval, which can't find the argument meansdf. Does anyone know how I can successfully pass the function argument to ggplot?

(Note: Yes I could just call the ggplot function directly, but in the end I hope to make my plot function do more complicated stuff! :) )

解决方案

As Joris and Chase have already correctly answered, standard best practice is to simply omit the meansdf$ part and directly refer to the data frame columns.

testplot <- function(meansdf)
{
  p <- ggplot(meansdf, 
              aes(fill = condition,
                  y = means,
                  x = condition))
  p + geom_bar(position = "dodge", stat = "identity")
}

This works, because the variables referred to in aes are looked for either in the global environment or in the data frame passed to ggplot. That is also the reason why your example code - using meansdf$condition etc. - did not work: meansdf is neither available in the global environment, nor is it available inside the data frame passed to ggplot, which is meansdf itself.

---

The fact that the variables are looked for in the global environment instead of in the calling environment is actually a known bug in ggplot2 that Hadley does not consider fixable at the moment. This leads to problems, if one wishes to use a local variable, say, scale, to influence the data used for the plot:

testplot <- function(meansdf)
{
  scale <- 0.5
  p <- ggplot(meansdf, 
              aes(fill = condition,
                  y = means * scale,   # does not work, since scale is not found
                  x = condition))
  p + geom_bar(position = "dodge", stat = "identity")
}

A very nice workaround for this case is provided by Winston Chang in the referenced GitHub issue: Explicitly setting the environment parameter to the current environment during the call to ggplot. Here's what that would look like for the above example:

testplot <- function(meansdf)
{
  scale <- 0.5
  p <- ggplot(meansdf, 
              aes(fill = condition,
                  y = means * scale,
                  x = condition),
              environment = environment())   # This is the only line changed / added
  p + geom_bar(position = "dodge", stat = "identity")
}

## Now, the following works
testplot(means)

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