remove lines if statements

Question

I have a data frame which looks like this:

Status  ID 
  A     1
  B     1
  B     1
  A     1
  B     1
  A     1
  A     2
  A     2
  A     2
  A     2
  B     3
  B     3
  B     3

To illustrate my desired output, please have a look at below:

Status  ID 
  B     1
  B     1
  B     1
  A     2
  A     2
  A     2
  A     2
  B     3
  B     3
  B     3

As you can see, the only thing that changes is for group ID = 1. If a group contains both a "A" and "B" status, I'd like to remove the "A" status.

However, Group ID 2 and 3 did not change (ie no lines removed) because: if each group ID only contains a "A", then it will remain the same. Likewise, if each group ID only contains a "B", it will also remain the same. Hence both remains the same.

Using dplyr, this is my attempt:

library(dplyr)

df1_clean <- df1 %>% group_by(ID, Status)
                 %>% filter(ifelse((Status == A | Status == B), Status == B,
                     ifelse((Status == A), Status == A,
                     ifelse((Status == B), Status == B))))

However, this filter will not work. Any help would be appreciated!

Answer 1

We can use filter grouped by ID

library(dplyr)
df %>%
  group_by(ID) %>%
  filter(all(Status == "A") | all(Status == "B") | Status == "B")

#   Status    ID
#   <fct>  <int>
# 1 B          1
# 2 B          1
# 3 B          1
# 4 A          2
# 5 A          2
# 6 A          2
# 7 A          2
# 8 B          3
# 9 B          3
#10 B          3

---

We can also use n_distinct

df %>%
  group_by(ID) %>%
  filter(n_distinct(Status) == 1 | Status == "B")

---

Equivalent base R ave versions would be

df[as.logical(with(df, ave(Status, ID, FUN = function(x) 
          all(x == "A") | all(x == "B") | x == "B"))), ]

df[as.logical(with(df, ave(Status, ID, FUN = function(x) 
         length(unique(x)) == 1 | x == "B"))), ]