how to use a logical vector in R [duplicate] - r

Question

This question already has answers here:
Remove groups that contain certain strings
(4 answers)
Closed 3 years ago.
3 doctors diagnose a patient
question 1 : how to filter the patient which all 3 doctors diagnose with disease B (no matter B.1, B.2 or B.3)
question 2: how to filter the patient which any of 3 doctors diagnose with disease A.
set.seed(20200107)
df <- data.frame(id = rep(1:5,each =3),
disease = sample(c('A','B'), 15, replace = T))
df$disease <- as.character(df$disease)
df[1,2] <- 'A'
df[4,2] <- 'B.1'
df[5,2] <- 'B.2'
df[6,2] <- 'B.3'·
df
I got a method but I don't know how to write the code. I think in the code any() or all() function shoule be used.
First, I want to group patients by id.
Second, check if all the disease is A or B in each group.
The code like this
df %>% group_by(id) %>% filter_all(all_vars(disease == B))

Answer 1

You can use all assuming every patient is checked by 3 doctors only.
library(dplyr)
df %>% group_by(id) %>% summarise(disease_B = all(grepl('B', disease)))
# id disease_B
# <int> <lgl>
#1 1 FALSE
#2 2 TRUE
#3 3 FALSE
#4 4 FALSE
#5 5 FALSE
If you want to subset the rows of the patient, we can use filter
df %>% group_by(id) %>% filter(all(grepl('B', disease)))
For question 2: similarly, we can use any
df %>% group_by(id) %>% summarise(disease_B = any(grepl('A', disease)))
data
df <- structure(list(id = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L,
4L, 4L, 5L, 5L, 5L), disease = c("A", "A", "A", "B.1", "B.2",
"B.3", "B", "A", "A", "B", "A", "A", "B", "A", "B")), row.names = c(NA,
-15L), class = "data.frame")

Answer 2

For the question 1, you can replace B.1 B.2 ... by B, then count the number of different "Disease" per patients and filter to keep only those equal to 3 and B:
library(tidyverse)
df %>% group_by(id) %>%
mutate(Disease = gsub(".[0-9]+","",disease)) %>%
count(Disease) %>%
filter(n == 3 & Disease == "B")
# A tibble: 2 x 3
# Groups: id [2]
id Disease n
<int> <chr> <int>
1 2 B 3
2 4 B 3
For the question 2, similarly, you can replace B.1 ... by B, then filter all rows with Disease is A, then count the number of rows per patients and your output is the patient id and the number of doctors that diagnose the disease A:
df %>% group_by(id) %>%
mutate(Disease = gsub(".[0-9]+","",disease))%>%
filter(Disease == "A") %>%
count(id)
# A tibble: 3 x 2
# Groups: id [3]
id n
<int> <int>
1 1 1
2 3 3
3 5 2