计算变量的唯一级别数 [英] Count number of unique levels of a variable

问题描述

我正在尝试一种简单的方法来计算数据框的一列中不同类别的数量.

I am trying to get a simple way to count the number of distinct categories in a column of a dataframe.

例如，在虹膜数据框中，有150行，其中一列是种类，其中有3种不同的种类.我希望能够运行这段代码，并确定该列中有3种不同的种类.我不在乎每个唯一条目对应多少行，只是有多少个不同的变量，这主要是我在研究中发现的.

For example, in the iris data frame, there are 150 rows with one of the columns being species, of which there are 3 different species. I want to be able to run this bit of code and determine that there are 3 different species in that column. I do not care how many rows each of those unique entries correspond to, just how many distinct variables there are, which is mostly what I found in my research.

我在想这样的事情:

df <- iris
choices <- count(unique(iris$Species))

是否存在像这样简单的解决方案?我看了这些帖子，但是它们要么检查整个数据框架，而不是检查该数据框架中的单个列，要么提供比我期望的更复杂的解决方案.

Does a solution as simple as this exist? I have looked at these posts, but they either examine the entire data frame rather than a single column in that data frame or provide a more complicated solution than what I am hoping for.

计数数据帧中实例的数量

分类变量的出现次数在数据框中(R)

>如何计数数据子集中的唯一字符向量数量

推荐答案

以下应完成该工作:

choices <- length(unique(iris$Species))

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