step.md
In dtplyr: Data Table Back-End for 'dplyr'

has useful display methods

Code
  dt <- lazy_dt(mtcars, "DT")
  dt
Output
  Source: local data table [32 x 11]
  Call:   DT

      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
  1  21       6   160   110  3.9   2.62  16.5     0     1     4     4
  2  21       6   160   110  3.9   2.88  17.0     0     1     4     4
  3  22.8     4   108    93  3.85  2.32  18.6     1     1     4     1
  4  21.4     6   258   110  3.08  3.22  19.4     1     0     3     1
  5  18.7     8   360   175  3.15  3.44  17.0     0     0     3     2
  6  18.1     6   225   105  2.76  3.46  20.2     1     0     3     1
  # ... with 26 more rows

  # Use as.data.table()/as.data.frame()/as_tibble() to access results
Code
  dt %>% group_by(vs, am)
Output
  Source: local data table [32 x 11]
  Groups: vs, am
  Call:   DT

      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
  1  21       6   160   110  3.9   2.62  16.5     0     1     4     4
  2  21       6   160   110  3.9   2.88  17.0     0     1     4     4
  3  22.8     4   108    93  3.85  2.32  18.6     1     1     4     1
  4  21.4     6   258   110  3.08  3.22  19.4     1     0     3     1
  5  18.7     8   360   175  3.15  3.44  17.0     0     0     3     2
  6  18.1     6   225   105  2.76  3.46  20.2     1     0     3     1
  # ... with 26 more rows

  # Use as.data.table()/as.data.frame()/as_tibble() to access results
Code
  dt %>% mutate(y = 10) %>% compute("DT2")
Output
  Source: local data table [32 x 12]
  Call:
    DT2 <- copy(DT)[, `:=`(y = 10)]
    DT2

      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb     y
    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
  1  21       6   160   110  3.9   2.62  16.5     0     1     4     4    10
  2  21       6   160   110  3.9   2.88  17.0     0     1     4     4    10
  3  22.8     4   108    93  3.85  2.32  18.6     1     1     4     1    10
  4  21.4     6   258   110  3.08  3.22  19.4     1     0     3     1    10
  5  18.7     8   360   175  3.15  3.44  17.0     0     0     3     2    10
  6  18.1     6   225   105  2.76  3.46  20.2     1     0     3     1    10
  # ... with 26 more rows

  # Use as.data.table()/as.data.frame()/as_tibble() to access results