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Suggestion for get_dupes: return additional variable "dupe_group" #371

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jeffmun opened this issue Apr 30, 2020 · 5 comments
Open

Suggestion for get_dupes: return additional variable "dupe_group" #371

jeffmun opened this issue Apr 30, 2020 · 5 comments
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seeking comments Users and any interested parties should please weigh in - this is in a discussion phase!

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@jeffmun
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jeffmun commented Apr 30, 2020

Feature request

I use get_dupes() all the time. Thank you!
I would find it very helpful to index each set of dupes with an additional variable.
Something like "dupe_group" or "dupe_index"?

In the code below, I've use frank to create the variable I am looking for, but it would be great to have this automatically embedded into get_dupes().

Thanks for your work on janitor.


The following illustrates what I'm thinking of:

# insert reprex here
library(data.table)
mydupes <- mtcars %>% get_dupes(cyl, gear)
mydupes$dupe_group <- frank(mydupes, cyl, gear, ties.method = "dense")
mydupes %>% dplyr::select(cyl, gear, dupe_count, dupe_group) 

This returns the following:
Having the "dupe_group" variable lets me immediately operate on each set of duplicates.

# A tibble: 30 x 4
     cyl  gear dupe_count dupe_group
   <dbl> <dbl>      <int>      <int>
 1     4     4          8          1
 2     4     4          8          1
 3     4     4          8          1
 4     4     4          8          1
 5     4     4          8          1
 6     4     4          8          1
 7     4     4          8          1
 8     4     4          8          1
 9     4     5          2          2
10     4     5          2          2
11     6     3          2          3
12     6     3          2          3
13     6     4          4          4
14     6     4          4          4
15     6     4          4          4
16     6     4          4          4
17     8     3         12          5
18     8     3         12          5
19     8     3         12          5
20     8     3         12          5
21     8     3         12          5
22     8     3         12          5
23     8     3         12          5
24     8     3         12          5
25     8     3         12          5
26     8     3         12          5
27     8     3         12          5
28     8     3         12          5
29     8     5          2          6
30     8     5          2          6
@sfirke sfirke added the seeking comments Users and any interested parties should please weigh in - this is in a discussion phase! label Apr 30, 2020
@sfirke
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sfirke commented Apr 30, 2020

I like this idea! I don't think it would be hard to implement either, any of these would probably do it: https://stackoverflow.com/questions/6112803/how-to-create-a-consecutive-index-based-on-a-grouping-variable-in-a-dataframe. We probably ought to test them for performance but dplyr::group_indices looks simple (I don't wish to add data.table as a dependency of janitor).

Any thoughts from other users, either in terms of how to implement this or how it should work for the user?

@jzadra
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jzadra commented Apr 30, 2020

I think this is a nice idea as well. And super easy to implement with probably zero performance hit.

I'd wonder if it should be default or require an argument to get the output? I suggest the latter, as I think it isn't useful to most people unless they specifically want it in order to accomplish something. add_dupe_group_index = F maybe.

Here's the way I've just tested that seems super simple and shouldn't add any noticeable performance decrease:

  1. filter dupe_count > 1 in line 37 code rather than on line 44.
  2. Add row_number to counts.

Sorry for not doing a PR, my git2r stopped working with ssh again and I don't have time to get it running right now.

get_dupes <- function(dat, ..., add_dupe_index = FALSE) {
  
  expr <- rlang::expr(c(...))
  pos <- tidyselect::eval_select(expr, data = dat)
  
  names(dat)[pos] <- names(pos) #allows for renaming within get_dupes() consistent with select()
  
  if (rlang::dots_n(...) == 0) { # if no tidyselect variables are specified, check the whole data.frame
    var_names <- names(dat)
    nms <- rlang::syms(var_names)
    message("No variable names specified - using all columns.\n")
  } else {
    var_names <- names(pos)
    nms <- rlang::syms(var_names)
  }
  
  dupe_count <- NULL # to appease NOTE for CRAN; does nothing.
  
  # calculate counts to join back to main df
  counts <- dat %>%
    dplyr::count(!!! nms, name = "dupe_count") %>% 
    filter(dupe_count > 1)
  
  if(add_dupe_index) counts <- counts %>% mutate(dupe_group = row_number())
  
  # join new count vector to main data.frame
  dupes <- suppressMessages(dplyr::inner_join(counts, dat))
  
  dupes <- dupes %>%
    dplyr::ungroup() %>%
    dplyr::arrange(!!! nms)
  
  # shorten error message for large data.frames
  if (length(var_names) > 10) {
    var_names <- c(var_names[1:9], paste("... and", length(var_names) - 9, "other variables"))
  }
  if (nrow(dupes) == 0) {
    message(paste0("No duplicate combinations found of: ", paste(var_names, collapse = ", ")))
  }
  dupes
}

And now:

> mtcars %>% select(cyl, gear) %>% get_dupes(cyl, gear)
   cyl gear dupe_count
1    4    4          8
2    4    4          8
3    4    4          8
4    4    4          8
5    4    4          8
6    4    4          8
7    4    4          8
8    4    4          8
9    4    5          2
10   4    5          2
11   6    3          2
12   6    3          2
13   6    4          4
14   6    4          4
15   6    4          4
16   6    4          4
17   8    3         12
18   8    3         12
19   8    3         12
20   8    3         12
21   8    3         12
22   8    3         12
23   8    3         12
24   8    3         12
25   8    3         12
26   8    3         12
27   8    3         12
28   8    3         12
29   8    5          2
30   8    5          2
> mtcars %>% select(cyl, gear) %>% get_dupes(cyl, gear, add_dupe_index = T)
   cyl gear dupe_count dupe_group
1    4    4          8          1
2    4    4          8          1
3    4    4          8          1
4    4    4          8          1
5    4    4          8          1
6    4    4          8          1
7    4    4          8          1
8    4    4          8          1
9    4    5          2          2
10   4    5          2          2
11   6    3          2          3
12   6    3          2          3
13   6    4          4          4
14   6    4          4          4
15   6    4          4          4
16   6    4          4          4
17   8    3         12          5
18   8    3         12          5
19   8    3         12          5
20   8    3         12          5
21   8    3         12          5
22   8    3         12          5
23   8    3         12          5
24   8    3         12          5
25   8    3         12          5
26   8    3         12          5
27   8    3         12          5
28   8    3         12          5
29   8    5          2          6
30   8    5          2          6

@higgi13425
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This sounds like a good idea. Would it make sense to add a function like keep_first_dupe(), that would keep only the first occurrence of each duplicated observation? That is something I find myself doing fairly often...

@jzadra
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jzadra commented Feb 4, 2022

I think it's easier just to follow it up with distinct(), unless I'm missing something?

@higgi13425
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higgi13425 commented Feb 4, 2022 via email

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