Functions for creating id column and key.

use_id(.tbl)

compute_id_name(x)

add_id(.tbl)

key_by_id(.tbl, .add = FALSE, .exclude = FALSE)

Arguments

.tbl

Reference data frame.

x

Character vector of names.

.add, .exclude

Parameters for key_by().

Details

use_id() assigns as keys a tibble with column '.id' and row numbers of .tbl as values.

compute_id_name() computes the name which is different from every element in x by the following algorithm: if '.id' is not present in x it is returned; if taken - '.id1' is checked; if taken - '.id11' is checked and so on.

add_id() creates a column with unique name (computed with compute_id_name()) and row numbers as values (grouping is ignored). After that puts it as first column.

key_by_id() is similar to add_id(): it creates a column with unique name and row numbers as values (grouping is ignored) and calls key_by() function to use this column as key. If .add is FALSE unique name is computed based on .tbl column names; if TRUE then based on .tbl and its keys column names.

Examples

mtcars %>% use_id()
#> # A keyed object. Keys: .id #> 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
mtcars %>% add_id()
#> .id mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 1 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 2 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 #> Datsun 710 3 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 #> Hornet 4 Drive 4 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 #> Hornet Sportabout 5 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> Valiant 6 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 #> Duster 360 7 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 8 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> Merc 230 9 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> Merc 280 10 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> Merc 280C 11 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> Merc 450SE 12 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 #> Merc 450SL 13 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 #> Merc 450SLC 14 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 #> Cadillac Fleetwood 15 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 #> Lincoln Continental 16 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 #> Chrysler Imperial 17 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 #> Fiat 128 18 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 #> Honda Civic 19 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> Toyota Corolla 20 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 #> Toyota Corona 21 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 #> Dodge Challenger 22 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> AMC Javelin 23 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> Camaro Z28 24 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 #> Pontiac Firebird 25 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> Fiat X1-9 26 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 #> Porsche 914-2 27 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> Lotus Europa 28 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> Ford Pantera L 29 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> Ferrari Dino 30 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 #> Maserati Bora 31 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 #> Volvo 142E 32 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
mtcars %>% key_by_id(.exclude = TRUE)
#> # A keyed object. Keys: .id #> 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