Analogous function for count
and add_count
in dplyr.
count_dt(data, ..., sort = TRUE, name = "n") add_count_dt(data, ..., name = "n")
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". |
data.table
iris %>% count_dt(Species)#> Species n #> <fctr> <int> #> 1: setosa 50 #> 2: versicolor 50 #> 3: virginica 50iris %>% count_dt(Species,name = "count")#> Species count #> <fctr> <int> #> 1: setosa 50 #> 2: versicolor 50 #> 3: virginica 50iris %>% 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 50iris %>% 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 50mtcars %>% 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 1mtcars %>% 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