循环在 ddply 中创建新变量
我正在使用 ddply 来聚合和汇总数据框变量，并且我有兴趣循环遍历数据框的列表以创建新变量。
new.data <- ddply(old.data,
c("factor", "factor2"),
function(df)
c(a11_a10 = CustomFunction(df$a11_a10),
a12_a11 = CustomFunction(df$a12_a11),
a13_a12 = CustomFunction(df$a13_a12),
...
...
...))
有没有办法让我在 ddply 中插入一个循环，这样我就可以避免写出每个新的摘要变量，例如
for (i in 11:n) {
paste("a", i, "_a", i - 1) = CustomFunction(..... )
}
我知道这不是实际完成的方式，但我只是想展示我如何概念化它。有没有办法在我在 ddply 中调用的函数中或通过列表来执行此操作？
更新：因为我是新用户，所以我无法发布自己问题的答案：
我的答案涉及 Nick 的答案和 Ista 的评论中的想法：
func <- function(old.data, min, max, gap) {
varrange <- min:max
usenames <- paste("a", varrange, "_a", varrange - gap, sep="")
new.data <- ddply(old.data,
.(factor, factor2),
colwise(CustomFunction, c(usenames)))
}
I am using ddply to aggregate and summarize data frame variables, and I am interested in looping through my data frame's list to create the new variables.
new.data <- ddply(old.data,
c("factor", "factor2"),
function(df)
c(a11_a10 = CustomFunction(df$a11_a10),
a12_a11 = CustomFunction(df$a12_a11),
a13_a12 = CustomFunction(df$a13_a12),
...
...
...))
Is there a way for me to insert a loop in ddply so that I can avoid writing each new summary variable out, e.g.
for (i in 11:n) {
paste("a", i, "_a", i - 1) = CustomFunction(..... )
}
I know that this is not how it would actually be done, but I just wanted to show how I'd conceptualize it. Is there a way to do this in the function I call in ddply, or via a list?
UPDATE: Because I'm a new user, I can't post an answer to my own question:
My answer involves ideas from Nick's answer and Ista's comment:
func <- function(old.data, min, max, gap) {
varrange <- min:max
usenames <- paste("a", varrange, "_a", varrange - gap, sep="")
new.data <- ddply(old.data,
.(factor, factor2),
colwise(CustomFunction, c(usenames)))
}
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评论（3）
基于 @Nick 的出色回答，这是解决该问题的一种方法
。这是一个使用 ggplot2 中的
tips数据集的示例应用程序。假设我们想通过sex和smoker的组合来计算tip和total_bill的平均值，以下是代码可以工作它会产生如下所示的输出
这是您正在寻找的吗？
Building on the excellent answer by @Nick, here is one approach to the problem
Here is an example application using the
tipsdataset inggplot2. Suppose we want to calculate the average oftipandtotal_billby combination ofsexandsmoker, here is how the code would workIt produces the output shown below
Is this what you were looking for?
如果我理解正确的话，您本质上是想将自定义函数应用于 ddply 数据框架中的每一列。
好消息是有一个 ddply 函数可以做到这一点。这意味着问题的解决方案可以归结为一句话：
以 @Ramnath 的优秀示例为基础：
它起作用的原因是
colwise将一个作用于向量的函数转换为一个作用于向量的函数在 data.frame 中的列上。colwise有两种变体：numcolwise仅适用于数字列，catcolwise适用于分类列。请参阅?colwise了解更多信息。编辑：
我理解您可能不希望将该函数应用于 data.frame 中的所有列。不过，我发现这种语法非常简单，我的一般方法是修改传递给 ddply 的 data.frame。例如，以下修改示例子集
tips以排除某些列。解决方案仍然是一句话：If I understand you correctly, you essentially want to apply a custom function to every column in the
ddplydata.frame.The good news is there is a
ddplyfunction that does exactly that. This means the solution to your problem boils down to a one liner:Building on the excellent example of @Ramnath:
The reason this works is that
colwiseturns a function that works on a vector into a function that works on a column in a data.frame. There are two variants ofcolwise:numcolwiseworks only on numeric columns, andcatcolwiseworks on categorical columns. See?colwisefor more information.EDIT:
I appreciate that you may not wish to apply the function to all columns in your data.frame. Still, I find this syntax so easy, that my general approach would be to modify the data.frame that I pass to
ddply. For example, the following modified example subsetstipsto exclude some columns. The solution is still a one-liner:步骤：
这是你想要的吗？
In steps:
Is this what you want?