How can I identify and extract duplicates from data frame? - r

Question

My objective is to check if a patient is using two drugs at the same date.
In the example, patient 1 is using drug A and drug B at the same date, but I want to extract it with code.
df <- data.frame(id = c(1,1,1,2,2,2),
date = c("2020-02-01","2020-02-01","2020-03-02","2019-10-02","2019-10-18","2019-10-26"),
drug_type = c("A","B","A","A","A","B"))
df$date <- as.factor(df$date)
df$drug_type <- as.factor(df$drug_type)
In order to do this, I firstly made date and drug type factor variables.
Next I used following code:
df %>%
mutate(lev_actdate = as.factor(actdate))%>%
filter(nlevels(drug_type)>1 & nlevels(date) < nrow(date))
But I failed. I assumed that if a patient is using two drugs at the same date, the number of levels in the date column will be less than its row number. However, now I don't know how to make it with code.
Additionally, I feel weird about following:
if I use nlevels(df$date), right result will be returned, but when I use df %>% nlevels(date), the error will be return with showing
"Error in nlevels(., df$date) : unused argument (df$date)"
Could you please tell me why this occurred and how can I fix it?
Thank you for your time.

Answer 1

You could use something like
library(dplyr)
df %>%
group_by(id, date) %>%
filter(n_distinct(drug_type) >= 2)
df %>% nlevels(date) is the same as nlevels(df, date) which is not the same as nlevels(df$date). Instead of the latter youcould try df %>% nlevels(.$date) or perhaps df %>% {nlevels(.$date)}.

Answer 2

Do you need something like this?
library(dplyr)
df %>%
group_by(date) %>%
distinct() %>%
summarise(drug_type_sum = toString(drug_type))
date drug_type_sum
<fct> <chr>
1 2019-10-02 A
2 2019-10-18 A
3 2019-10-26 B
4 2020-02-01 A, B
5 2020-03-02 A