Group a data frame and add per-group indices as a column.

add_group_indices(.data, groupingVars, indexColumn)

Arguments

.data	data.frame
groupingVars	character vector of column names to group by.
indexColumn	character name of column to add indices to.

Value

.data with group identifying column added.

Examples


add_group_indices(datasets::mtcars, c("cyl", "gear"), 'groupID')
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb groupID
#> 1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4       5
#> 2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4       5
#> 3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1       2
#> 4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1       4
#> 5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2       7
#> 6  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1       4
#> 7  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4       7
#> 8  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2       2
#> 9  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2       2
#> 10 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4       5
#> 11 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4       5
#> 12 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3       7
#> 13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3       7
#> 14 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3       7
#> 15 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4       7
#> 16 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4       7
#> 17 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4       7
#> 18 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1       2
#> 19 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2       2
#> 20 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1       2
#> 21 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1       1
#> 22 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2       7
#> 23 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2       7
#> 24 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4       7
#> 25 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2       7
#> 26 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1       2
#> 27 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2       3
#> 28 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2       3
#> 29 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4       8
#> 30 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6       6
#> 31 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8       8
#> 32 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2       2