dplyr计数一个特定变量值的数量 [英] dplyr count number of one specific value of variable

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问题描述

说我有一个像这样的数据集:

  id <-c(1、2、2、3 ,3)
代码<-c( a, b, a, a, b, b)
dat<--data.frame(id ,代码)

即,

  id代码
1 1 a
2 1 b
3 2 a
4 2 a
5 3 b
6 3 b

使用dplyr,我如何计算每个id有多少个



即,

  id countA 
1 1 1
2 2 2
3 3 0

我正在尝试这样的东西

  countA<-dat%>%
group_by(id)%>%
summarise(cip.completed =计数(code == a))

以上给我一个错误,错误:没有将'group_by_'的适用方法应用于逻辑类的对象。



感谢您的帮助!

解决方案

请尝试以下操作:

  library(dplyr)
dat%>%group_by(id )%>%
summarise(cip.completed = sum(code == a)))

来源:本地数据帧[3 x 2]
id cip。已完成
(dbl)(int)
1 1 1
2 2 2
3 3 0

之所以有用,是因为逻辑条件 code == a 只是一系列零和一,而该系列的总和为发生次数。



请注意,您不必在摘要 dplyr :: count c $ c>无论如何,因为它是总结的包装,因此调用 n() sum()本身。请参见?dplyr :: count 。如果您真的想使用 count ,我想您可以通过首先过滤数据集以仅保留 code == a ,然后使用 count 将为您提供所有严格为正(即非零)的计数。例如,

  dat%>%filter(code == a)%>%count(id)

来源:本地数据帧[2 x 2]

id n
(dbl)(int)
1 1 1
2 2 2


Say I have a dataset like this:

id <- c(1, 1, 2, 2, 3, 3)
code <- c("a", "b", "a", "a", "b", "b")
dat <- data.frame(id, code)

I.e.,

    id  code
1   1   a
2   1   b 
3   2   a
4   2   a
5   3   b
6   3   b

Using dplyr, how would I get a count of how many a's there are for each id

i.e.,

   id  countA
1   1   1
2   2   2
3   3   0

I'm trying stuff like this which isn't working,

countA<- dat %>%
group_by(id) %>%
summarise(cip.completed= count(code == "a"))

The above gives me an error, "Error: no applicable method for 'group_by_' applied to an object of class "logical""

Thanks for your help!

解决方案

Try the following instead:

library(dplyr)
dat %>% group_by(id) %>%
  summarise(cip.completed= sum(code == "a"))

Source: local data frame [3 x 2]
    id cip.completed
  (dbl)         (int)
1     1             1
2     2             2
3     3             0

This works because the logical condition code == a is just a series of zeros and ones, and the sum of this series is the number of occurences.

Note that you would not necessarily use dplyr::count inside summarise anyway, as it is a wrapper for summarise calling either n() or sum() itself. See ?dplyr::count. If you really want to use count, I guess you could do that by first filtering the dataset to only retain all rows in which code==a, and using count would then give you all strictly positive (i.e. non-zero) counts. For instance,

dat %>% filter(code==a) %>% count(id)

Source: local data frame [2 x 2]

     id     n
  (dbl) (int)
1     1     1
2     2     2

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