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tidyfst1.8.2

Count observations by group

Source:R/count_dt.R
count.Rd

Count the unique values of one or more variables.

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

Arguments

.data

data.table/data.frame data.frame will be automatically convertedto data.table.

...

Variables to group by, could receive what `select_dt` receives.

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

count

Examples

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)#>      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    50iris%>%add_count_dt(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    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%>%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%>%count_dt(cyl,vs,.name="N",sort=FALSE)#>      cyl    vs     N#>    <num> <num> <int>#> 1:     6     0     3#> 2:     4     1    10#> 3:     6     1     4#> 4:     8     0    14#> 5:     4     0     1mtcars%>%add_count_dt(cyl,vs)#>       mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear#>     <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#>  2:  21.0     6 160.0   110  3.90 2.875 17.02     0     1     4#>  3:  22.8     4 108.0    93  3.85 2.320 18.61     1     1     4#>  4:  21.4     6 258.0   110  3.08 3.215 19.44     1     0     3#>  5:  18.7     8 360.0   175  3.15 3.440 17.02     0     0     3#>  6:  18.1     6 225.0   105  2.76 3.460 20.22     1     0     3#>  7:  14.3     8 360.0   245  3.21 3.570 15.84     0     0     3#>  8:  24.4     4 146.7    62  3.69 3.190 20.00     1     0     4#>  9:  22.8     4 140.8    95  3.92 3.150 22.90     1     0     4#> 10:  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4#> 11:  17.8     6 167.6   123  3.92 3.440 18.90     1     0     4#> 12:  16.4     8 275.8   180  3.07 4.070 17.40     0     0     3#> 13:  17.3     8 275.8   180  3.07 3.730 17.60     0     0     3#> 14:  15.2     8 275.8   180  3.07 3.780 18.00     0     0     3#> 15:  10.4     8 472.0   205  2.93 5.250 17.98     0     0     3#> 16:  10.4     8 460.0   215  3.00 5.424 17.82     0     0     3#> 17:  14.7     8 440.0   230  3.23 5.345 17.42     0     0     3#> 18:  32.4     4  78.7    66  4.08 2.200 19.47     1     1     4#> 19:  30.4     4  75.7    52  4.93 1.615 18.52     1     1     4#> 20:  33.9     4  71.1    65  4.22 1.835 19.90     1     1     4#> 21:  21.5     4 120.1    97  3.70 2.465 20.01     1     0     3#> 22:  15.5     8 318.0   150  2.76 3.520 16.87     0     0     3#> 23:  15.2     8 304.0   150  3.15 3.435 17.30     0     0     3#> 24:  13.3     8 350.0   245  3.73 3.840 15.41     0     0     3#> 25:  19.2     8 400.0   175  3.08 3.845 17.05     0     0     3#> 26:  27.3     4  79.0    66  4.08 1.935 18.90     1     1     4#> 27:  26.0     4 120.3    91  4.43 2.140 16.70     0     1     5#> 28:  30.4     4  95.1   113  3.77 1.513 16.90     1     1     5#> 29:  15.8     8 351.0   264  4.22 3.170 14.50     0     1     5#> 30:  19.7     6 145.0   175  3.62 2.770 15.50     0     1     5#> 31:  15.0     8 301.0   335  3.54 3.570 14.60     0     1     5#> 32:  21.4     4 121.0   109  4.11 2.780 18.60     1     1     4#>       mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear#> 2 variable(s) not shown: [carb <num>, n <int>]mtcars%>%add_count_dt("cyl|vs")#>       mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear#>     <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#>  2:  21.0     6 160.0   110  3.90 2.875 17.02     0     1     4#>  3:  22.8     4 108.0    93  3.85 2.320 18.61     1     1     4#>  4:  21.4     6 258.0   110  3.08 3.215 19.44     1     0     3#>  5:  18.7     8 360.0   175  3.15 3.440 17.02     0     0     3#>  6:  18.1     6 225.0   105  2.76 3.460 20.22     1     0     3#>  7:  14.3     8 360.0   245  3.21 3.570 15.84     0     0     3#>  8:  24.4     4 146.7    62  3.69 3.190 20.00     1     0     4#>  9:  22.8     4 140.8    95  3.92 3.150 22.90     1     0     4#> 10:  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4#> 11:  17.8     6 167.6   123  3.92 3.440 18.90     1     0     4#> 12:  16.4     8 275.8   180  3.07 4.070 17.40     0     0     3#> 13:  17.3     8 275.8   180  3.07 3.730 17.60     0     0     3#> 14:  15.2     8 275.8   180  3.07 3.780 18.00     0     0     3#> 15:  10.4     8 472.0   205  2.93 5.250 17.98     0     0     3#> 16:  10.4     8 460.0   215  3.00 5.424 17.82     0     0     3#> 17:  14.7     8 440.0   230  3.23 5.345 17.42     0     0     3#> 18:  32.4     4  78.7    66  4.08 2.200 19.47     1     1     4#> 19:  30.4     4  75.7    52  4.93 1.615 18.52     1     1     4#> 20:  33.9     4  71.1    65  4.22 1.835 19.90     1     1     4#> 21:  21.5     4 120.1    97  3.70 2.465 20.01     1     0     3#> 22:  15.5     8 318.0   150  2.76 3.520 16.87     0     0     3#> 23:  15.2     8 304.0   150  3.15 3.435 17.30     0     0     3#> 24:  13.3     8 350.0   245  3.73 3.840 15.41     0     0     3#> 25:  19.2     8 400.0   175  3.08 3.845 17.05     0     0     3#> 26:  27.3     4  79.0    66  4.08 1.935 18.90     1     1     4#> 27:  26.0     4 120.3    91  4.43 2.140 16.70     0     1     5#> 28:  30.4     4  95.1   113  3.77 1.513 16.90     1     1     5#> 29:  15.8     8 351.0   264  4.22 3.170 14.50     0     1     5#> 30:  19.7     6 145.0   175  3.62 2.770 15.50     0     1     5#> 31:  15.0     8 301.0   335  3.54 3.570 14.60     0     1     5#> 32:  21.4     4 121.0   109  4.11 2.780 18.60     1     1     4#>       mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear#> 2 variable(s) not shown: [carb <num>, n <int>]

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