Analogous function for count and add_count in dplyr.

count_dt(data, ..., sort = TRUE, name = "n")

add_count_dt(data, ..., name = "n")

Arguments

data

data.table/data.frame data.frame will be automatically converted to data.table.

...

variables to group by.

sort

logical. If TRUE result will be sorted in desending order by resulting variable.

name

character. Name of resulting variable. Default uses "n".

Value

data.table

See also

Examples

iris %>% count_dt(Species)
#> Species n #> <fctr> <int> #> 1: setosa 50 #> 2: versicolor 50 #> 3: virginica 50
iris %>% count_dt(Species,name = "count")
#> Species count #> <fctr> <int> #> 1: setosa 50 #> 2: versicolor 50 #> 3: virginica 50
iris %>% add_count_dt(Species)
#> Species Sepal.Length Sepal.Width Petal.Length Petal.Width n #> <fctr> <num> <num> <num> <num> <int> #> 1: setosa 5.1 3.5 1.4 0.2 50 #> 2: setosa 4.9 3.0 1.4 0.2 50 #> 3: setosa 4.7 3.2 1.3 0.2 50 #> 4: setosa 4.6 3.1 1.5 0.2 50 #> 5: setosa 5.0 3.6 1.4 0.2 50 #> --- #> 146: virginica 6.7 3.0 5.2 2.3 50 #> 147: virginica 6.3 2.5 5.0 1.9 50 #> 148: virginica 6.5 3.0 5.2 2.0 50 #> 149: virginica 6.2 3.4 5.4 2.3 50 #> 150: virginica 5.9 3.0 5.1 1.8 50
iris %>% add_count_dt(Species,name = "N")
#> Species Sepal.Length Sepal.Width Petal.Length Petal.Width N #> <fctr> <num> <num> <num> <num> <int> #> 1: setosa 5.1 3.5 1.4 0.2 50 #> 2: setosa 4.9 3.0 1.4 0.2 50 #> 3: setosa 4.7 3.2 1.3 0.2 50 #> 4: setosa 4.6 3.1 1.5 0.2 50 #> 5: setosa 5.0 3.6 1.4 0.2 50 #> --- #> 146: virginica 6.7 3.0 5.2 2.3 50 #> 147: virginica 6.3 2.5 5.0 1.9 50 #> 148: virginica 6.5 3.0 5.2 2.0 50 #> 149: virginica 6.2 3.4 5.4 2.3 50 #> 150: virginica 5.9 3.0 5.1 1.8 50
mtcars %>% count_dt(cyl,vs)
#> cyl vs n #> <num> <num> <int> #> 1: 8 0 14 #> 2: 4 1 10 #> 3: 6 1 4 #> 4: 6 0 3 #> 5: 4 0 1
mtcars %>% add_count_dt(cyl,vs)
#> cyl vs mpg disp hp drat wt qsec am gear carb n #> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num> <int> #> 1: 6 0 21.0 160.0 110 3.90 2.620 16.46 1 4 4 3 #> 2: 6 0 21.0 160.0 110 3.90 2.875 17.02 1 4 4 3 #> 3: 6 0 19.7 145.0 175 3.62 2.770 15.50 1 5 6 3 #> 4: 4 1 22.8 108.0 93 3.85 2.320 18.61 1 4 1 10 #> 5: 4 1 24.4 146.7 62 3.69 3.190 20.00 0 4 2 10 #> 6: 4 1 22.8 140.8 95 3.92 3.150 22.90 0 4 2 10 #> 7: 4 1 32.4 78.7 66 4.08 2.200 19.47 1 4 1 10 #> 8: 4 1 30.4 75.7 52 4.93 1.615 18.52 1 4 2 10 #> 9: 4 1 33.9 71.1 65 4.22 1.835 19.90 1 4 1 10 #> 10: 4 1 21.5 120.1 97 3.70 2.465 20.01 0 3 1 10 #> 11: 4 1 27.3 79.0 66 4.08 1.935 18.90 1 4 1 10 #> 12: 4 1 30.4 95.1 113 3.77 1.513 16.90 1 5 2 10 #> 13: 4 1 21.4 121.0 109 4.11 2.780 18.60 1 4 2 10 #> 14: 6 1 21.4 258.0 110 3.08 3.215 19.44 0 3 1 4 #> 15: 6 1 18.1 225.0 105 2.76 3.460 20.22 0 3 1 4 #> 16: 6 1 19.2 167.6 123 3.92 3.440 18.30 0 4 4 4 #> 17: 6 1 17.8 167.6 123 3.92 3.440 18.90 0 4 4 4 #> 18: 8 0 18.7 360.0 175 3.15 3.440 17.02 0 3 2 14 #> 19: 8 0 14.3 360.0 245 3.21 3.570 15.84 0 3 4 14 #> 20: 8 0 16.4 275.8 180 3.07 4.070 17.40 0 3 3 14 #> 21: 8 0 17.3 275.8 180 3.07 3.730 17.60 0 3 3 14 #> 22: 8 0 15.2 275.8 180 3.07 3.780 18.00 0 3 3 14 #> 23: 8 0 10.4 472.0 205 2.93 5.250 17.98 0 3 4 14 #> 24: 8 0 10.4 460.0 215 3.00 5.424 17.82 0 3 4 14 #> 25: 8 0 14.7 440.0 230 3.23 5.345 17.42 0 3 4 14 #> 26: 8 0 15.5 318.0 150 2.76 3.520 16.87 0 3 2 14 #> 27: 8 0 15.2 304.0 150 3.15 3.435 17.30 0 3 2 14 #> 28: 8 0 13.3 350.0 245 3.73 3.840 15.41 0 3 4 14 #> 29: 8 0 19.2 400.0 175 3.08 3.845 17.05 0 3 2 14 #> 30: 8 0 15.8 351.0 264 4.22 3.170 14.50 1 5 4 14 #> 31: 8 0 15.0 301.0 335 3.54 3.570 14.60 1 5 8 14 #> 32: 4 0 26.0 120.3 91 4.43 2.140 16.70 1 5 2 1 #> cyl vs mpg disp hp drat wt qsec am gear carb n