如何将10列收集到一列中，将其他10列收集到另一个列中，仅在tidyverse中计数和频率，在R中

Question

我在与合并症相关的几列以及与症状相关的其他列上进行双重收集时遇到麻烦。目的是获得每组合并症和症状的计数和频率。

这是我拥有的数据类型。

 test <- structure(
  list(
    ID = c("1",
           "2", "3",
           "4", "5",
           "6"),
    Chills = c("No", "Mild", "No", "Mild", "No", "No"),
    Cough = c("No", "Severe", "No", "Mild", "Mild", "No"),
    Diarrhoea = c("No", "Mild", "No", "No", "No", "No"),
    Fatigue = c("No", "Moderate", "Mild", "Mild", "Mild", "Mild"),
    Headcahe = c("No", "No", "No", "Mild", "No", "No"),
    `Loss of smell and taste` = c("No", "No", "No", "No", "No", "No"),
    `Muscle Ache` = c("No", "Moderate", "No", "Moderate", "Mild", "Mild"),
    `Nasal Congestion` = c("No", "No", "No", "No", "Mild", "No"),
    `Nausea and Vomiting` = c("No", "No",
                              "No", "No", "No", "No"),
    `Shortness of Breath` = c("No",
                              "Mild", "No", "No", "No", "Mild"),
    `Sore Throat` = c("No",
                      "No", "No", "No", "Mild", "No"),
    Sputum = c("No", "Mild",
               "No", "Mild", "Mild", "No"),
    Temperature = c("No", "No",
                    "No", "No", "No", "37.5-38"),
    Comorbidity_one = c(
      "Asthma (managed with an inhaler)",
      "None",
      "Obesity",
      "High Blood Pressure (hypertension)",
      "None",
      "None"
    ),
    Comorbidity_two = c("Diabetes Type 2", NA,
                        NA, "Obesity", NA, NA),
    Comorbidity_three = c(
      "Asthma (managed with an inhaler)",
      "None",
      "Obesity",
      "High Blood Pressure (hypertension)",
      "None",
      NA_character_
    ),
    Comorbidity_four = c(
      "Asthma (managed with an inhaler)",
      "None",
      "High Blood Pressure (hypertension)",
      NA_character_,
      NA_character_,
      NA_character_
    ),
    Comorbidity_five = c(
      "Asthma (managed with an inhaler)",
      "None",
      NA_character_,
      NA_character_,
      NA_character_,
      NA_character_
    ),
    Comorbidity_six = c(
      NA_character_,
      NA_character_,
      NA_character_,
      NA_character_,
      NA_character_,
      NA_character_
    ),
    Comorbidity_seven = c(
      NA_character_,
      NA_character_,
      NA_character_,
      NA_character_,
      NA_character_,
      NA_character_
    ),
    Comorbidity_eight = c(
      "High Blood Pressure (hypertension)",
      NA_character_,
      NA_character_,
      NA_character_,
      NA_character_,
      NA_character_
    ),
    Comorbidity_nine = c(
      NA_character_,
      NA_character_,
      NA_character_,
      "High Blood Pressure (hypertension)",
      NA_character_,
      "High Blood Pressure (hypertension)"
    )
  ),
  row.names = c(NA,-6L),
  class = c("tbl_df",
            "tbl", "data.frame")
)

但是输出的对象只是一个样本，应该看起来像这样：

 structure(list(Comorbidities = c("Asthma", "Asthma", "Asthma", 
"Diabetes", "Diabetes", "Diabetes", "High blood Pressure", "High blood Pressure", 
"High blood Pressure"), Symptoms = c("Cough", "Cough", "Loss of smell and taste", 
"Cough", "Chills mild", "Loss of smell and taste", "Cough", "Chills", 
"Loss of smell and taste"), Group = c("Mild", "Moderate", "Severe", 
"Mild", "Moderate", "Severe", "Mild", "Moderate", "Severe"), 
    Count = c(112, 10, 10, 123, 132, 153, 897, 98, 10), Percentage = c(0.23, 
    0.3, 0.1, 0.6, 0.5, 0.3, 0.8, 0.9, 0.5)), row.names = c(NA, 
-9L), class = c("tbl_df", "tbl", "data.frame"))

我只想用R中的tidyverse来实现。

Answer 1

也许这就是您所追求的。我首先将更长的时间分别用于症状，然后再用于合并症，如果没有，则省略记录。百分比是每种发病率中症状的数量。如果这不是您想要的，则可以轻松更改它。

library(tidyr)

pivot_longer(test, cols=2:14, names_to=c("symptom"),
             values_to="severity") %>%
  filter(severity!="No") %>%
  pivot_longer(cols=starts_with("Comorbidity"), 
               names_to=c("name","time"), names_sep="_",
               values_to="morbidity") %>%
  filter(morbidity != "None") %>%
  group_by(morbidity, symptom, severity) %>%
  summarise(Count=n()) %>%
  group_by(morbidity) %>%
  mutate(Percentage=Count/sum(Count))
___
# A tibble: 15 x 5
# Groups:   morbidity [2]
   morbidity                          symptom             severity Count Percentage
   <chr>                              <chr>               <chr>    <int>      <dbl>
 1 High Blood Pressure (hypertension) Chills              Mild         3     0.130 
 2 High Blood Pressure (hypertension) Cough               Mild         3     0.130 
 3 High Blood Pressure (hypertension) Fatigue             Mild         5     0.217 
 4 High Blood Pressure (hypertension) Headcahe            Mild         3     0.130 
 5 High Blood Pressure (hypertension) Muscle Ache         Mild         1     0.0435
 6 High Blood Pressure (hypertension) Muscle Ache         Moderate     3     0.130 
 7 High Blood Pressure (hypertension) Shortness of Breath Mild         1     0.0435
 8 High Blood Pressure (hypertension) Sputum              Mild         3     0.130 
 9 High Blood Pressure (hypertension) Temperature         37.5-38      1     0.0435
10 Obesity                            Chills              Mild         1     0.125 
11 Obesity                            Cough               Mild         1     0.125 
12 Obesity                            Fatigue             Mild         3     0.375 
13 Obesity                            Headcahe            Mild         1     0.125 
14 Obesity                            Muscle Ache         Moderate     1     0.125 
15 Obesity                            Sputum              Mild         1     0.125