如何计算数据子集内唯一字符向量的数量

问题描述

以下是我的数据集示例：

Here is an example of my dataset:

Dput -

（已删除）

我按照这个代码按月分组这个数据框：

And I am subsetting this data frame by month using this code:

simpleindoor.mean <- simple_trapindoors %>% group_by(month) %>% summarise(n=n(),mean = mean(bitingrate), stderror = std(bitingrate))

其中产生如下表格：

  |Month| n |   mean| stderror|
  |-----|---|-------|---------|                          
  |May  | 12|   0.25|     0.13|
  |June | 21|   0.53|     0.12|
  |July | 21|   0.53|     0.12|

我想做的是在同一功能中计算每个月内个人FAMILY_ID的数量，并将其添加为simpleindoor.mean的新列。

What I would like to do is calculate the number of individual FAMILY_ID's within each month in the same function, and add it as a new column to "simpleindoor.mean".

FAMILY_ID是一个字符向量。例如 6001-032。因此，如果在5月份有12个独特的FAMILY_ID，则新的数据列将在匹配May的行中显示12个。

FAMILY_ID is a character vector. E.g."6001-032". So if there were 12 unique FAMILY_ID's in May, the new column of data would show 12 in the row matching "May".

我已经看到了一些例子，您可以在其中查找字符向量的特定实例，但是我很难找到一个例子，您可以在其中计算出在特定组。我如何做？

I have seen examples where you look for specific instances of a character vector, but I struggled to find an example where you can count the instances of unique character vectors occurring within a particular group. How do I do this?

谢谢。

推荐答案

你需要 n_distinct

simple_trapindoors %>% group_by(month) %>% summarise(n=n(),mean = mean(bitingrate), stderror = std(bitingrate), 
                                                     UniqueFamilies = n_distinct(FAMILY_ID))

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