在带有cut2的pretty_breaks时避免空的和小的组 [英] Avoiding empty and small groups when using pretty_breaks with cut2

问题描述

我正在使用类似于下面创建的数据 val 值的变量：

I'm working with variables resembling the data val values created below:

# data --------------------------------------------------------------------

data("mtcars")
val <- c(mtcars$wt, 10.55) 

我按以下方式剪切此变量：

I'm cutting this variable in the following manner:

# Cuts --------------------------------------------------------------------

cut_breaks <- pretty_breaks(n = 10, eps.correct = 0)(val)
res <- cut2(x = val, cuts = cut_breaks)

会产生以下结果：

> table(res)
res
[ 1, 2) [ 2, 3) [ 3, 4) [ 4, 5) [ 5, 6)       6       7       8       9 [10,11] 
      4       8      16       1       3       0       0       0       0       1

在创建的输出中，我想更改以下内容：

In the created output I would like to change the following:

• 我对创建具有一个值的组没有兴趣。理想情况下，我希望每个组至少具有3/4的值。矛盾的是，我可以保留具有0值的组，因为这些组以后在合并我的真实数据时会掉落。


• 对剪切机制的任何更改都必须使用处理变量整数值


• 剪切必须漂亮。我试图避免出现类似1.23-2.35的情况。即使考虑到分布，这些值将是最明智的。


• 实际上，我要实现的目标是：试图使或多或少的人变得漂亮，并且
。

• I'm not interested in creating grups with one value. Ideally, I would like to for each group to have at least 3 / 4 values. Paradoxically, I can leave with groups having 0 values as those will dropped later on when mergining on my real data
• Any changes to the cutting mechanism, have to work on a variable with integer values
• The cuts have to be pretty. I'm trying to avoid something like 1.23 - 2.35. Even if those values would be most sensible considering the distribution.
• In effect, what I'm trying to achieve is this: try to make more or less even pretty group and if getting a really tiny group then bump it together with the next group, do not worry about empty groups.

为方便起见，完整代码如下：

For convenience, the full code is available below:

# Libs --------------------------------------------------------------------

   Vectorize(require)(package = c("scales", "Hmisc"),
                      character.only = TRUE)


   # data --------------------------------------------------------------------

   data("mtcars") val <- c(mtcars$wt, 10.55) 

   # Cuts --------------------------------------------------------------------

   cut_breaks <- pretty_breaks(n = 10, eps.correct = 0)(val) res <-
   cut2(x = val, cuts = cut_breaks)

---

我尝试过的事情

第一种方法

我尝试玩 eps.correct = 0 pretty_breaks 中的c $ c>值，如代码中所示：

---

What I've tried

First approach

I tried to play with the eps.correct = 0 value in the pretty_breaks like in the code:

cut_breaks <- pretty_breaks(n = cuts, eps.correct = 0)(variable)

但没有的值使我到某个地方很近

but none of the values gets me anwhere were close

我也尝试过使用<$ c在 cut2 函数中使用$ c> m = 5 自变量，但我一直得到相同的结果。

I've also tried using the m= 5 argument in the cut2 function but I keep on arriving at the same result.

我尝试了 mybreaks 函数，但我必须对它进行一些工作才能获得更多精简变量的有效削减。概括地说， pretty_breaks 对我来说很不错，因为不希望偶尔出现的小团体。

I tried the mybreaks function but I would have to put some work into it to get nice cuts for more bizzare variables. Broadly speaking, pretty_breaks cuts well for me, juts the tiny groups that occur from time to time are not desired.

> set.seed(1); require(scales)
> mybreaks <- function(x, n, r=0) {
+   unique(round(quantile(x, seq(0, 1, length=n+1)), r))
+ }
> x <- runif(n = 100)
> pretty_breaks(n = 5)(x)
[1] 0.0 0.2 0.4 0.6 0.8 1.0
> mybreaks(x = x, n = 5)
[1] 0 1

推荐答案

您可以使用 quantile（）函数作为相对简单的方法来获取每个组中相似数量的观测值。

You could use the quantile() function as a relatively easy way to get similar numbers of observations in each of your groups.

例如，下面的函数采用值 x 的向量，所需数量的组 n ，并为中断指定所需的舍入点 r ，并为您提供建议的切入点。

For example, here's a function that takes a vector of values x, a desired number of groups n, and a desired rounding off point r for the breaks, and gives you suggested cut points.

mybreaks <- function(x, n, r=0) {
  unique(round(quantile(x, seq(0, 1, length=n+1)), r))
}

cut_breaks  <- mybreaks(val, 5)
res <- cut(val, cut_breaks, include.lowest=TRUE)
table(res)

 [2,3]  (3,4] (4,11] 
     8     16      5 

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