根据布尔值分析分类数据

Question

我在 R 中有一个数据框，其中包含以下数据

> df3
    care_uncare              risks
1            No High risk patients
2           Yes High risk patients
3           Yes High risk patients
4           Yes High risk patients
5           Yes  Low risk patients
6           Yes  Low risk patients
7            No  Low risk patients
8           Yes High risk patients
9           Yes  Low risk patients
10          Yes  Low risk patients
11          Yes High risk patients
12          Yes  Low risk patients
13           No  Low risk patients
14          Yes  Low risk patients
15          Yes  Low risk patients
16          Yes High risk patients

其中 care_uncare 变量包含 Yes/No 值，风险变量包含高风险 patients/Low 风险患者。

我想生成一个摘要或可视化，显示 care_uncare 为 'Yes' 但有风险为 'High risk patients'

的患者总数

我该如何进行分析？

Answer 1

这可以很容易地用这个：

df3 %>% group_by(care_uncare, risks) %>% summarise( n = n() )

Answer 2

您可以使用 filter 和 summarise

library(dplyr)
df %>% filter(care_uncare == "Yes" & risks == "High risk patients") %>%
summarise( Total_Yes_High = n() )

  a     care_uncare risks             
  <chr> <chr>       <chr>             
1 2     Yes         High risk patients
2 3     Yes         High risk patients
3 4     Yes         High risk patients
4 8     Yes         High risk patients
5 11    Yes         High risk patients
6 16    Yes         High risk patients

根据布尔值分析分类数据

Analyse categorical data against boolean

analytics

r