如何在 R 中将 10 列收集到一个列中，将其他 10 列收集到另一个列中，计数和频率仅使用 tidyverse

Question

I am having a trouble in doing double gathering on several column that are related to Comorbidities, and other columns that are related to Symptoms. The purpose is to get a count and frequency per groups of comorbidities and symptoms.

This is the type of data I have.

 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")
)

But the outputted object, just a sample, should look like this:

 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"))

I want to achieve this only with tidyverse, in R.

Answer 1

Maybe this is what you're after. I pivot longer separately for symptoms first and then co-morbidities, omitting records if they have none. Percentages are the number of symptoms among each morbidity. If that's not what you want, you can easily change it.

library(tidyr); library(dplyr)

pivot_longer(test, cols=2:14, names_to="symptom", values_to="severity") %>%
  filter(severity!="No") %>%
  pivot_longer(cols=starts_with("Comorbidity"), 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