Remove IDs with fewer than 9 unique observations

Question

I am trying to filter my data and remove IDs that have fewer than 9 unique month observations. I would also like to create a list of IDs that includes the count.

I've tried using a few different options:

library(dplyr)
count <- bind %>% group_by(IDS) %>% filter(n(data.month)>= 9) %>%       ungroup()
count2 <- subset(bind, with(bind, IDS %in% names(which(table(data.month)>=9))))

Neither of these worked.

This is what my data looks like:

   data.month   ID
           01    2
           02    2
           03    2
           04    2
           05    2
           05    2
           06    2
           06    2
           07    2
           07    2
           07    2
           07    2
           07    2
           08    2
           09    2
           10    2
           11    2
           12    2
           01    5
           01    5
           02    5
           01    7
           01    7
           01    7
           01    4
           02    4
           03    4
           04    4
           05    4
           05    4
           06    4
           06    4
           07    4
           07    4
           07    4
           07    4
           07    4
           08    4
           09    4
           10    4
           11    4
           12    4

In the end, I would like a this:

IDs
2
3

I would also like this

IDs  Count
2     12
5     2
7     1
4     12

So far this code is the closest, but still just gives error codes:

count <- bind %>%
  group_by(IDs) %>% 
  filter(length(unique(bind$data.month >=9)))

Error in filter_impl(.data, quo) : Argument 2 filter condition does not evaluate to a logical vector

Answer 1

We can use n_distinct

To remove IDs with less than 9 unique observations

library(dplyr)

df %>%
  group_by(ID) %>%
  filter(n_distinct(data.month) >= 9) %>%
  pull(ID) %>% unique

#[1] 2 4

Or

df %>%
  group_by(ID) %>%
  filter(n_distinct(data.month) >= 9) %>%
  distinct(ID)

#     ID
#  <int>
#1     2
#2     4

---

For unique counts of each ID

df %>%
  group_by(ID) %>%
  summarise(count = n_distinct(data.month))


#     ID count
#   <int> <int>
#1     2    12
#2     4    12
#3     5     2
#4     7     1