Keep rows that are within specific interval for different conditions and grouped by

Question

Here's a reprex for illustration.

library(tidyverse)

set.seed(1337)
df <- tibble(
  date_visit = sample(seq(as.Date("2020/01/01"),
    as.Date("2021/01/01"),
    by = "day"
  ), 400, replace = T),
  patient_id = as.factor(paste("patient", sample(seq(1, 13), 400, replace = T), sep = "_")),
  type_of_visit = as.factor(sample(c("medical", "veterinary"), 400, replace = T))
)

What I'm trying to do create a dataframe where I keep the patient_id (group by, I assume), and the visit types if that patient has done 2 different visits in less than 24 hours. Or adding a variable that says True/False if that condition is met.

I tried to use a left join by patient_id to work with 2 different variables but that takes too much computing time (my original DF is much longer than this)

Can someone point me in the right direction?

Thank you

Answer 1

Maybe this will help -

library(dplyr)

df %>%
  group_by(patient_id, date_visit) %>%
  summarise(flag = n_distinct(type_of_visit) >= 2) %>%
  summarise(flag = any(flag))

#  patient_id flag 
#   <fct>      <lgl>
# 1 patient_1  TRUE 
# 2 patient_10 FALSE
# 3 patient_11 TRUE 
# 4 patient_12 FALSE
# 5 patient_13 FALSE
# 6 patient_2  FALSE
# 7 patient_3  FALSE
# 8 patient_4  FALSE
# 9 patient_5  TRUE 
#10 patient_6  FALSE
#11 patient_7  TRUE 
#12 patient_8  TRUE 
#13 patient_9  TRUE 

If you want to keep all the rows for those patient id's

df %>%
  group_by(patient_id, date_visit) %>%
  summarise(flag = n_distinct(type_of_visit) >= 2) %>%
  filter(any(flag))