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Union all elements of R objects together.

Usage

union_all(x, y, ...)

Arguments

x, y

objects to union all elements of (ignoring order)

...

other arguments passed on to methods

Examples

first <- mtcars[1:20, ]
second <- mtcars[10:32, ]
union_all(first, second)
#>                       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
#> Merc 2801            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
#> Merc 280C1           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
#> Merc 450SE1          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
#> Merc 450SL1          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
#> Merc 450SLC1         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
#> Cadillac Fleetwood1  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
#> Lincoln Continental1 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
#> Chrysler Imperial1   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
#> Fiat 1281            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
#> Honda Civic1         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
#> Toyota Corolla1      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

# union_all does not remove duplicates
a <- data.frame(column = c(1:10, 10))
b <- data.frame(column = c(1:5, 5))
union_all(a, b)
#>    column
#> 1       1
#> 2       2
#> 3       3
#> 4       4
#> 5       5
#> 6       6
#> 7       7
#> 8       8
#> 9       9
#> 10     10
#> 11     10
#> 12      1
#> 13      2
#> 14      3
#> 15      4
#> 16      5
#> 17      5