Determine the groups within a data.frame to perform operations on. ungroup() removes the grouping levels.

group_by(.data, ..., .add = FALSE)

ungroup(x, ...)

Arguments

.data

data.frame. The data to group.

...

One or more unquoted column names to group/ungroup the data by.

.add

logical(1). When FALSE (the default) group_by() will override existing groups. To add to existing groups, use .add = TRUE.

x

A data.frame.

Value

When using group_by(), a data.frame, grouped by the grouping variables.

When using ungroup(), a data.frame.

Examples

group_by(mtcars, am, cyl)
#> mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
ungroup(mutate(group_by(mtcars, am, cyl), sumMpg = sum(mpg)))
#> mpg cyl disp hp drat wt qsec vs am gear carb sumMpg #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 61.7 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 61.7 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 224.6 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 76.5 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 180.6 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 76.5 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 180.6 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 68.7 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 68.7 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 76.5 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 76.5 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 180.6 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 180.6 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 180.6 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 180.6 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 180.6 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 180.6 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 224.6 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 224.6 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 224.6 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 68.7 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 180.6 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 180.6 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 180.6 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 180.6 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 224.6 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 224.6 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 224.6 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 30.8 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 61.7 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 30.8 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 224.6
mtcars %>% group_by(am, cyl) %>% mutate(sumMpg = sum(mpg)) %>% ungroup()
#> mpg cyl disp hp drat wt qsec vs am gear carb sumMpg #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 61.7 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 61.7 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 224.6 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 76.5 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 180.6 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 76.5 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 180.6 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 68.7 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 68.7 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 76.5 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 76.5 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 180.6 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 180.6 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 180.6 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 180.6 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 180.6 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 180.6 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 224.6 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 224.6 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 224.6 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 68.7 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 180.6 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 180.6 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 180.6 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 180.6 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 224.6 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 224.6 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 224.6 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 30.8 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 61.7 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 30.8 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 224.6
mtcars %>% group_by(carb) %>% filter(any(gear == 5))
#> mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
# You can group by expressions: this is just short-hand for # a mutate() followed by a group_by() mtcars %>% group_by(vsam = vs + am)
#> mpg cyl disp hp drat wt qsec vs am gear carb vsam #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 1 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 1 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 2 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 1 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 0 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 1 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 0 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 1 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 1 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 1 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 1 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 0 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 0 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 0 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 0 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 0 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 0 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 2 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 2 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 2 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 1 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 0 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 0 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 0 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 0 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 2 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 1 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 2 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 1 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 1 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 1 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 2