The enhanced data.frame, including tibble and data.table, do not
support row names. To link to some base r facilities, there should be functions
to save information in row names. These functions are analogous to
rownames_to_column and column_to_rownames in tibble.
rn_col(.data, var = "rowname")
col_rn(.data, var = "rowname")A data.frame.
Name of column to use for rownames.
rn_col returns a data.table,
col_rn returns a data frame.
mtcars %>% rn_col()
#> rowname mpg cyl disp hp drat wt qsec vs am
#> <char> <num> <num> <num> <num> <num> <num> <num> <num> <num>
#> 1: Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1
#> 2: Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1
#> 3: Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1
#> 4: Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0
#> 5: Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0
#> 6: Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0
#> 7: Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0
#> 8: Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0
#> 9: Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0
#> 10: Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0
#> 11: Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0
#> 12: Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0
#> 13: Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0
#> 14: Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0
#> 15: Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0
#> 16: Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0
#> 17: Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0
#> 18: Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1
#> 19: Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1
#> 20: Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1
#> 21: Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0
#> 22: Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0
#> 23: AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0
#> 24: Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0
#> 25: Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0
#> 26: Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1
#> 27: Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1
#> 28: Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1
#> 29: Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1
#> 30: Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1
#> 31: Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1
#> 32: Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1
#> rowname mpg cyl disp hp drat wt qsec vs am
#> gear carb
#> <num> <num>
#> 1: 4 4
#> 2: 4 4
#> 3: 4 1
#> 4: 3 1
#> 5: 3 2
#> 6: 3 1
#> 7: 3 4
#> 8: 4 2
#> 9: 4 2
#> 10: 4 4
#> 11: 4 4
#> 12: 3 3
#> 13: 3 3
#> 14: 3 3
#> 15: 3 4
#> 16: 3 4
#> 17: 3 4
#> 18: 4 1
#> 19: 4 2
#> 20: 4 1
#> 21: 3 1
#> 22: 3 2
#> 23: 3 2
#> 24: 3 4
#> 25: 3 2
#> 26: 4 1
#> 27: 5 2
#> 28: 5 2
#> 29: 5 4
#> 30: 5 6
#> 31: 5 8
#> 32: 4 2
#> gear carb
mtcars %>% rn_col("rn")
#> rn mpg cyl disp hp drat wt qsec vs am
#> <char> <num> <num> <num> <num> <num> <num> <num> <num> <num>
#> 1: Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1
#> 2: Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1
#> 3: Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1
#> 4: Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0
#> 5: Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0
#> 6: Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0
#> 7: Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0
#> 8: Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0
#> 9: Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0
#> 10: Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0
#> 11: Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0
#> 12: Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0
#> 13: Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0
#> 14: Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0
#> 15: Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0
#> 16: Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0
#> 17: Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0
#> 18: Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1
#> 19: Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1
#> 20: Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1
#> 21: Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0
#> 22: Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0
#> 23: AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0
#> 24: Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0
#> 25: Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0
#> 26: Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1
#> 27: Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1
#> 28: Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1
#> 29: Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1
#> 30: Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1
#> 31: Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1
#> 32: Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1
#> rn mpg cyl disp hp drat wt qsec vs am
#> gear carb
#> <num> <num>
#> 1: 4 4
#> 2: 4 4
#> 3: 4 1
#> 4: 3 1
#> 5: 3 2
#> 6: 3 1
#> 7: 3 4
#> 8: 4 2
#> 9: 4 2
#> 10: 4 4
#> 11: 4 4
#> 12: 3 3
#> 13: 3 3
#> 14: 3 3
#> 15: 3 4
#> 16: 3 4
#> 17: 3 4
#> 18: 4 1
#> 19: 4 2
#> 20: 4 1
#> 21: 3 1
#> 22: 3 2
#> 23: 3 2
#> 24: 3 4
#> 25: 3 2
#> 26: 4 1
#> 27: 5 2
#> 28: 5 2
#> 29: 5 4
#> 30: 5 6
#> 31: 5 8
#> 32: 4 2
#> gear carb
mtcars %>% rn_col() -> new_mtcars
new_mtcars %>% col_rn() -> old_mtcars
old_mtcars
#> 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
setequal(mtcars,old_mtcars)
#> [1] TRUE