How to find number of unique ids corresponding to each date in a data drame

Question

I have a data frame that looks like this:

      date         time              id            datetime    
1 2015-01-02 14:27:22.130 999000000007628 2015-01-02 14         


        

Answer 1

This answer is in response to this post: group by and then count unique observations which was marked as duplicate as I was writing this draft. This is not in response to the question for the duplicate basis here: How to find number of unique ids corresponding to each date in a data drame which asks about finding unique ID's. I'm not sure the second post actually answers the OP's question which is,

"I want to create a table with the number of unique id for each combination of group1 and group2."

The keyword here is 'combination'. The interpretation is each id has a particular value for group1 and a particular value for group2 so that the set of data of interest is the particular set of values c(id, group1, group2).

Here is the data.frame the OP provided:

df1 <- data.frame(id=sample(letters, 10000, replace = T),
group1=sample(1:2, 10000, replace = T),
group2=sample(100:101, 10000, replace = T))

Using data.table inspired by this post -- https://stackoverflow.com/a/13017723/5220858:

>library(data.table)
>DT <- data.table(df1)
>DT[, .N, by = .(group1, group2)]

   group1 group2    N
1:      1    100 2493
2:      1    101 2455
3:      2    100 2559
4:      2    101 2493

N is the count for the id that has a particular group1 value and a particular group2 value. Expanding to include the id also returns a table of 104 unique id, group1, group2 combinations.

>DT[, .N, by = .(id, group1, group2)]

     id group1 group2   N
  1:  t      1    100 107
  2:  g      1    101  85
  3:  l      1    101  98
  4:  a      1    100  83
  5:  j      1    101  98
 ---                     
100:  p      1    101  96
101:  r      2    101  91
102:  y      1    101 104
103:  g      1    100  83
104:  r      2    100  77

Answer 2

You can use the uniqueN function from data.table:

library(data.table)
setDT(df)[, uniqueN(id), by = date]

or (as per the comment of @Richard Scriven):

aggregate(id ~ date, df, function(x) length(unique(x)))

Answer 3

Or we could use n_distinct from library(dplyr)

library(dplyr) 
df %>%
   group_by(date) %>%
   summarise(id=n_distinct(id))