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