This is a method for the dplyr arrange() generic. It is translated to
the i argument of [.data.table
Usage
# 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 toTRUEare 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: `_DT11`[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: `_DT11`[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: `_DT11`[`_DT11`[, .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