Analogous function for count and add_count in dplyr.

count(.data, ..., sort = FALSE, name = "n")

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

Arguments

.data

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

Examples

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