Subset rows using column values

Source: R/step-subset-filter.R

This is a method for the dplyr arrange() generic. It is translated to the i argument of [.data.table

# S3 method for dtplyr_step
filter(.data, ..., .preserve = FALSE)

Arguments

.data

A lazy_dt().
...

<data-masking> Expressions that return a logical value, and are defined in terms of the variables in .data. If multiple expressions are included, they are combined with the & operator. Only rows for which all conditions evaluate to TRUE are kept.
.preserve

Ignored

Examples

library(dplyr, warn.conflicts = FALSE)

dt <- lazy_dt(mtcars)
dt %>% filter(cyl == 4)

#> Source: local data table [11 x 11]
#> Call:   `_DT9`[cyl == 4]
#> 
#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1  22.8     4 108      93  3.85  2.32  18.6     1     1     4     1
#> 2  24.4     4 147.     62  3.69  3.19  20       1     0     4     2
#> 3  22.8     4 141.     95  3.92  3.15  22.9     1     0     4     2
#> 4  32.4     4  78.7    66  4.08  2.2   19.5     1     1     4     1
#> 5  30.4     4  75.7    52  4.93  1.62  18.5     1     1     4     2
#> 6  33.9     4  71.1    65  4.22  1.84  19.9     1     1     4     1
#> # … with 5 more rows
#> 
#> # Use as.data.table()/as.data.frame()/as_tibble() to access results
dt %>% filter(vs, am)

#> Source: local data table [7 x 11]
#> Call:   `_DT9`[vs & am]
#> 
#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1  22.8     4 108      93  3.85  2.32  18.6     1     1     4     1
#> 2  32.4     4  78.7    66  4.08  2.2   19.5     1     1     4     1
#> 3  30.4     4  75.7    52  4.93  1.62  18.5     1     1     4     2
#> 4  33.9     4  71.1    65  4.22  1.84  19.9     1     1     4     1
#> 5  27.3     4  79      66  4.08  1.94  18.9     1     1     4     1
#> 6  30.4     4  95.1   113  3.77  1.51  16.9     1     1     5     2
#> # … with 1 more row
#> 
#> # Use as.data.table()/as.data.frame()/as_tibble() to access results

dt %>%
  group_by(cyl) %>%
  filter(mpg > mean(mpg))

#> Source: local data table [16 x 11]
#> Groups: cyl
#> Call:   `_DT9`[`_DT9`[, .I[mpg > mean(mpg)], by = .(cyl)]$V1]
#> 
#>     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  21.4     6 258     110  3.08  3.22  19.4     1     0     3     1
#> 4  32.4     4  78.7    66  4.08  2.2   19.5     1     1     4     1
#> 5  30.4     4  75.7    52  4.93  1.62  18.5     1     1     4     2
#> 6  33.9     4  71.1    65  4.22  1.84  19.9     1     1     4     1
#> # … with 10 more rows
#> 
#> # Use as.data.table()/as.data.frame()/as_tibble() to access results