summarise ignoring .groups argument

[sbashevkin]

I've noticed that the summarise function used within a dtplyr pipline is ignoring the .groups argument and instead creating a new ".groups" column. When the .groups argument is left out, the resulting tibble doesn't retain any grouping, while base dplyr retains grouping for the first grouping column.

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(dtplyr)
#> Warning: package 'dtplyr' was built under R version 4.0.5

# Data
data<-tibble(group1=rep(1:2, each=3), group2=rep(3:4, each=3), value=1:6)

# With regular dplyr
data%>%
    group_by(group1, group2)%>%
    summarise(value_mean=mean(value), .groups="drop")
#> # A tibble: 2 x 3
#>   group1 group2 value_mean
#>    <int>  <int>      <dbl>
#> 1      1      3          2
#> 2      2      4          5

# With dtplyr, .groups argument is ignored and turned into a new column
data%>%
    lazy_dt()%>%
    group_by(group1, group2)%>%
    summarise(value_mean=mean(value), .groups="drop")%>%
    as_tibble()
#> # A tibble: 2 x 4
#>   group1 group2 value_mean .groups
#>    <int>  <int>      <dbl> <chr>  
#> 1      1      3          2 drop   
#> 2      2      4          5 drop

# With dtplyr without the .groups argument, grouping is still removed
data%>%
    lazy_dt()%>%
    group_by(group1, group2)%>%
    summarise(value_mean=mean(value))%>%
    as_tibble()
#> # A tibble: 2 x 3
#>   group1 group2 value_mean
#>    <int>  <int>      <dbl>
#> 1      1      3          2
#> 2      2      4          5

# Whereas the same pipeline with just dplyr would preserve grouping
data%>%
    group_by(group1, group2)%>%
    summarise(value_mean=mean(value))
#> `summarise()` has grouped output by 'group1'. You can override using the `.groups` argument.
#> # A tibble: 2 x 3
#> # Groups:   group1 [2]
#>   group1 group2 value_mean
#>    <int>  <int>      <dbl>
#> 1      1      3          2
#> 2      2      4          5

^{Created on 2021-05-18 by the reprex package (v2.0.0)}

Session info

sessioninfo::session_info()
#> - Session info ---------------------------------------------------------------
#>  setting  value                       
#>  version  R version 4.0.3 (2020-10-10)
#>  os       Windows 10 x64              
#>  system   x86_64, mingw32             
#>  ui       RTerm                       
#>  language (EN)                        
#>  collate  English_United States.1252  
#>  ctype    English_United States.1252  
#>  tz       America/Los_Angeles         
#>  date     2021-05-18                  
#> 
#> - Packages -------------------------------------------------------------------
#>  package     * version date       lib source        
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#>  backports     1.2.1   2020-12-09 [1] CRAN (R 4.0.3)
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#>  dtplyr      * 1.1.0   2021-02-20 [1] CRAN (R 4.0.5)
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#> 
#> [1] C:/Users/sbashevkin/Documents/R/R-4.0.3/library

[mgirlich]

I added support for the .groups argument in this PR.
Note that as_tibble() drops the grouping. This was a breaking change in tibble 2.0, see News. To keep the grouping you have to use collect().