r - 仅对疑似类别的患者进行了多少次测试，R

Question

我有可重现的例子。我有重复的 ID。有些怀疑有些没有。

structure(list(id = c(1, 1, 1, 2, 2, 3, 3, 4, 4, 4), test = c("susp", 
"susp", "neg", "pos", "pos", "neg", "pos", "susp", "susp", "neg"
)), row.names = c(NA, -10L), class = c("tbl_df", "tbl", "data.frame"
))

然而，我有兴趣获得计数:

疑似患者总数

被怀疑跟随多次测试的那些客户端不管结果。

想要对那些有两个和三个疑似的人进行总数。

注意事项!!如果这可以通过 tidyverse 完成，那将是惊人的。
表格外观示例，请参见下文。

structure(list(id = c(1, 4), number_of_test_for_suspected_pat = c(2, 
2)), row.names = c(NA, -2L), class = c("tbl_df", "tbl", "data.frame"
))

并额外与一共疑似患者进行后续测试。

Answer 1

我们可以filter输出没有任何“疑似”病例的“id”，然后得到 sum逻辑`向量

library(dplyr)
df1 %>%
    group_by(id) %>% 
    filter('susp' %in% test) %>% 
    summarise(number_of_test_for_suspected_pat = sum(test == 'susp'),
    n_greater_than_3 = number_of_test_for_suspected_pat >=3) %>%
     mutate(Total = sum(number_of_test_for_suspected_pat), 
         n_greater_than_3_count = sum(n_greater_than_3))
# A tibble: 2 x 5
#     id number_of_test_for_suspected_pat n_greater_than_3 Total n_greater_than_3_count
#  <dbl>                            <int> <lgl>            <int>                  #<int>
#1     1                                2 FALSE                4                      0
#2     4                                2 FALSE                4                      0

或者做 filter第一的

df1 %>%
   filter(test == 'susp') %>%
   count(id) %>%
   mutate(Total = sum(n))