如何结合 count() 和 group_by() 来计算具有特定值的响应，按受访者分组？

Question

我有一组数据，其中对一系列重复问题的回答是感兴趣的结果。因此，我想计算“我不知道”回复的数量，按受访者 ID 对这些计数进行分组，并将其作为新列追加。所以基本上，我的数据如下所示：

ID	response
1	Yes
1	I don't know
2	No
2	I don't know

我希望它们看起来像这样：

ID	response	idkcount
1	Yes	1
1	I don't know	1
2	No	1
2	I don't know	1

这是我最近写的代码：

df$idkcount <- group_by(as_tibble(df$ID)) %>% count(df$response == "I don't know")

但是无论我用这两个命令尝试什么，我似乎都会收到一条错误消息。我错过了什么？

Answer 1

使用 group_by 和 mutate 你可以：

注意：我将您的示例数据稍微修改为更一般的情况。

df <- data.frame(
  ID = c(1L, 1L, 1L, 1L, 2L, 2L),
  response = c("Yes", "I don't know", "I don't know", "I don't know", "No", "I don't know")
)

library(dplyr)

df %>% 
  group_by(ID) %>% 
  mutate(idkcount = sum(response == "I don't know", na.rm = TRUE)) %>% 
  ungroup()
#> # A tibble: 6 × 3
#>      ID response     idkcount
#>   <int> <chr>           <int>
#> 1     1 Yes                 3
#> 2     1 I don't know        3
#> 3     1 I don't know        3
#> 4     1 I don't know        3
#> 5     2 No                  1
#> 6     2 I don't know        1

Answer 2

my_df <- data.frame("id" = c(1, 1, 2, 2, 3),
                "response" = c("I don't know", "I don't know", "no", "I don't know", "maybe"),
                stringsAsFactors = FALSE)

my_df <- my_df %>% group_by(id) %>% mutate(count = length(which(response == "I don't know")))

Answer 3

可能的解决方案（我正在使用@stefan 的数据集）：

library(tidyverse)

df <- data.frame(
  ID = c(1L, 1L, 1L, 1L, 2L, 2L),
  response = c("Yes", "I don't know", "I don't know", "I don't know", "No", "I don't know")
)

df %>% 
  count(ID, response, name = "idkcount")

#>   ID     response idkcount
#> 1  1 I don't know        3
#> 2  1          Yes        1
#> 3  2 I don't know        1
#> 4  2           No        1

如何结合 count() 和 group_by() 来计算具有特定值的响应，按受访者分组？

How to combine count() and group_by() to count responses with a certain value, grouped by respondent?

r

plyr

dplyr