Vertically Combine Data Frames by Intersect
bind.RdFor bind_intersect(): rbind() is used to vertically combine data
frames based on the intersect of their column names.
This creates fewer columns than the original data, or at best the same
number of columns. The resulting data frame has the dimensions:
rows:
nrow(df1) + nrow(df2) + ... + nrow(df_n)cols:
intersect(names(...))
For bind_union(): rbind() is used to vertically merge
data frames based on the union of their column names. This creates
columns of NAs for the rows of a data frame with non-overlapping
column names. The resulting data frame has the dimensions:
rows:
nrow(df1) + nrow(df2) + ... + nrow(df_n)cols:
union(names(...))
Details
Incidentally, the default behavior of rbind() reorders the columns
correctly, but will only do so if their intersect matches.
Note
For bind_intersect(), columns are combined on
their intersect only.
For bind_union(), the ordering of the rows correspond
to the order they are supplied.
Examples
# For `bind_intersect()`
spl <- split(mtcars, mtcars$cyl) |> unname()
foo <- mapply(spl, -c(11, 10, 9), FUN = function(x, y) x[, y], SIMPLIFY = FALSE)
sapply(spl, names)
#> [,1] [,2] [,3]
#> [1,] "mpg" "mpg" "mpg"
#> [2,] "cyl" "cyl" "cyl"
#> [3,] "disp" "disp" "disp"
#> [4,] "hp" "hp" "hp"
#> [5,] "drat" "drat" "drat"
#> [6,] "wt" "wt" "wt"
#> [7,] "qsec" "qsec" "qsec"
#> [8,] "vs" "vs" "vs"
#> [9,] "am" "am" "am"
#> [10,] "gear" "gear" "gear"
#> [11,] "carb" "carb" "carb"
sapply(spl, ncol)
#> [1] 11 11 11
# Pass a list
bind_intersect(spl)
#> data mpg cyl disp hp drat wt qsec vs am
#> Datsun 710 data_01 22.8 4 108.0 93 3.85 2.320 18.61 1 1
#> Merc 240D data_01 24.4 4 146.7 62 3.69 3.190 20.00 1 0
#> Merc 230 data_01 22.8 4 140.8 95 3.92 3.150 22.90 1 0
#> Fiat 128 data_01 32.4 4 78.7 66 4.08 2.200 19.47 1 1
#> Honda Civic data_01 30.4 4 75.7 52 4.93 1.615 18.52 1 1
#> Toyota Corolla data_01 33.9 4 71.1 65 4.22 1.835 19.90 1 1
#> Toyota Corona data_01 21.5 4 120.1 97 3.70 2.465 20.01 1 0
#> Fiat X1-9 data_01 27.3 4 79.0 66 4.08 1.935 18.90 1 1
#> Porsche 914-2 data_01 26.0 4 120.3 91 4.43 2.140 16.70 0 1
#> Lotus Europa data_01 30.4 4 95.1 113 3.77 1.513 16.90 1 1
#> Volvo 142E data_01 21.4 4 121.0 109 4.11 2.780 18.60 1 1
#> Mazda RX4 data_02 21.0 6 160.0 110 3.90 2.620 16.46 0 1
#> Mazda RX4 Wag data_02 21.0 6 160.0 110 3.90 2.875 17.02 0 1
#> Hornet 4 Drive data_02 21.4 6 258.0 110 3.08 3.215 19.44 1 0
#> Valiant data_02 18.1 6 225.0 105 2.76 3.460 20.22 1 0
#> Merc 280 data_02 19.2 6 167.6 123 3.92 3.440 18.30 1 0
#> Merc 280C data_02 17.8 6 167.6 123 3.92 3.440 18.90 1 0
#> Ferrari Dino data_02 19.7 6 145.0 175 3.62 2.770 15.50 0 1
#> Hornet Sportabout data_03 18.7 8 360.0 175 3.15 3.440 17.02 0 0
#> Duster 360 data_03 14.3 8 360.0 245 3.21 3.570 15.84 0 0
#> Merc 450SE data_03 16.4 8 275.8 180 3.07 4.070 17.40 0 0
#> Merc 450SL data_03 17.3 8 275.8 180 3.07 3.730 17.60 0 0
#> Merc 450SLC data_03 15.2 8 275.8 180 3.07 3.780 18.00 0 0
#> Cadillac Fleetwood data_03 10.4 8 472.0 205 2.93 5.250 17.98 0 0
#> Lincoln Continental data_03 10.4 8 460.0 215 3.00 5.424 17.82 0 0
#> Chrysler Imperial data_03 14.7 8 440.0 230 3.23 5.345 17.42 0 0
#> Dodge Challenger data_03 15.5 8 318.0 150 2.76 3.520 16.87 0 0
#> AMC Javelin data_03 15.2 8 304.0 150 3.15 3.435 17.30 0 0
#> Camaro Z28 data_03 13.3 8 350.0 245 3.73 3.840 15.41 0 0
#> Pontiac Firebird data_03 19.2 8 400.0 175 3.08 3.845 17.05 0 0
#> Ford Pantera L data_03 15.8 8 351.0 264 4.22 3.170 14.50 0 1
#> Maserati Bora data_03 15.0 8 301.0 335 3.54 3.570 14.60 0 1
#> gear carb
#> Datsun 710 4 1
#> Merc 240D 4 2
#> Merc 230 4 2
#> Fiat 128 4 1
#> Honda Civic 4 2
#> Toyota Corolla 4 1
#> Toyota Corona 3 1
#> Fiat X1-9 4 1
#> Porsche 914-2 5 2
#> Lotus Europa 5 2
#> Volvo 142E 4 2
#> Mazda RX4 4 4
#> Mazda RX4 Wag 4 4
#> Hornet 4 Drive 3 1
#> Valiant 3 1
#> Merc 280 4 4
#> Merc 280C 4 4
#> Ferrari Dino 5 6
#> Hornet Sportabout 3 2
#> Duster 360 3 4
#> Merc 450SE 3 3
#> Merc 450SL 3 3
#> Merc 450SLC 3 3
#> Cadillac Fleetwood 3 4
#> Lincoln Continental 3 4
#> Chrysler Imperial 3 4
#> Dodge Challenger 3 2
#> AMC Javelin 3 2
#> Camaro Z28 3 4
#> Pontiac Firebird 3 2
#> Ford Pantera L 5 4
#> Maserati Bora 5 8
# Can pass either list or via '...'
identical(bind_intersect(spl), bind_intersect(spl[[1L]], spl[[2L]], spl[[3L]]))
#> [1] TRUE
# Passing a *named* list adds `data` column with those names
names(spl) <- letters[1:3L]
bind_intersect(spl)
#> data mpg cyl disp hp drat wt qsec vs am gear
#> Datsun 710 a 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4
#> Merc 240D a 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4
#> Merc 230 a 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4
#> Fiat 128 a 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4
#> Honda Civic a 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4
#> Toyota Corolla a 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4
#> Toyota Corona a 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3
#> Fiat X1-9 a 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4
#> Porsche 914-2 a 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5
#> Lotus Europa a 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5
#> Volvo 142E a 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4
#> Mazda RX4 b 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4
#> Mazda RX4 Wag b 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4
#> Hornet 4 Drive b 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3
#> Valiant b 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3
#> Merc 280 b 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4
#> Merc 280C b 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4
#> Ferrari Dino b 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5
#> Hornet Sportabout c 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3
#> Duster 360 c 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3
#> Merc 450SE c 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3
#> Merc 450SL c 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3
#> Merc 450SLC c 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3
#> Cadillac Fleetwood c 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3
#> Lincoln Continental c 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3
#> Chrysler Imperial c 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3
#> Dodge Challenger c 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3
#> AMC Javelin c 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3
#> Camaro Z28 c 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3
#> Pontiac Firebird c 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3
#> Ford Pantera L c 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5
#> Maserati Bora c 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5
#> carb
#> Datsun 710 1
#> Merc 240D 2
#> Merc 230 2
#> Fiat 128 1
#> Honda Civic 2
#> Toyota Corolla 1
#> Toyota Corona 1
#> Fiat X1-9 1
#> Porsche 914-2 2
#> Lotus Europa 2
#> Volvo 142E 2
#> Mazda RX4 4
#> Mazda RX4 Wag 4
#> Hornet 4 Drive 1
#> Valiant 1
#> Merc 280 4
#> Merc 280C 4
#> Ferrari Dino 6
#> Hornet Sportabout 2
#> Duster 360 4
#> Merc 450SE 3
#> Merc 450SL 3
#> Merc 450SLC 3
#> Cadillac Fleetwood 4
#> Lincoln Continental 4
#> Chrysler Imperial 4
#> Dodge Challenger 2
#> AMC Javelin 2
#> Camaro Z28 4
#> Pontiac Firebird 2
#> Ford Pantera L 4
#> Maserati Bora 8
# For `bind_union()`
bind_union(spl)
#> data mpg cyl disp hp drat wt qsec vs am gear
#> Datsun 710 a 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4
#> Merc 240D a 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4
#> Merc 230 a 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4
#> Fiat 128 a 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4
#> Honda Civic a 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4
#> Toyota Corolla a 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4
#> Toyota Corona a 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3
#> Fiat X1-9 a 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4
#> Porsche 914-2 a 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5
#> Lotus Europa a 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5
#> Volvo 142E a 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4
#> Mazda RX4 b 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4
#> Mazda RX4 Wag b 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4
#> Hornet 4 Drive b 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3
#> Valiant b 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3
#> Merc 280 b 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4
#> Merc 280C b 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4
#> Ferrari Dino b 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5
#> Hornet Sportabout c 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3
#> Duster 360 c 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3
#> Merc 450SE c 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3
#> Merc 450SL c 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3
#> Merc 450SLC c 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3
#> Cadillac Fleetwood c 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3
#> Lincoln Continental c 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3
#> Chrysler Imperial c 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3
#> Dodge Challenger c 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3
#> AMC Javelin c 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3
#> Camaro Z28 c 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3
#> Pontiac Firebird c 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3
#> Ford Pantera L c 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5
#> Maserati Bora c 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5
#> carb
#> Datsun 710 1
#> Merc 240D 2
#> Merc 230 2
#> Fiat 128 1
#> Honda Civic 2
#> Toyota Corolla 1
#> Toyota Corona 1
#> Fiat X1-9 1
#> Porsche 914-2 2
#> Lotus Europa 2
#> Volvo 142E 2
#> Mazda RX4 4
#> Mazda RX4 Wag 4
#> Hornet 4 Drive 1
#> Valiant 1
#> Merc 280 4
#> Merc 280C 4
#> Ferrari Dino 6
#> Hornet Sportabout 2
#> Duster 360 4
#> Merc 450SE 3
#> Merc 450SL 3
#> Merc 450SLC 3
#> Cadillac Fleetwood 4
#> Lincoln Continental 4
#> Chrysler Imperial 4
#> Dodge Challenger 2
#> AMC Javelin 2
#> Camaro Z28 4
#> Pontiac Firebird 2
#> Ford Pantera L 4
#> Maserati Bora 8
bind_union(spl[[1L]], spl[[2L]])
#> data mpg cyl disp hp drat wt qsec vs am gear
#> Datsun 710 data_01 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4
#> Merc 240D data_01 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4
#> Merc 230 data_01 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4
#> Fiat 128 data_01 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4
#> Honda Civic data_01 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4
#> Toyota Corolla data_01 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4
#> Toyota Corona data_01 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3
#> Fiat X1-9 data_01 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4
#> Porsche 914-2 data_01 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5
#> Lotus Europa data_01 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5
#> Volvo 142E data_01 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4
#> Mazda RX4 data_02 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4
#> Mazda RX4 Wag data_02 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4
#> Hornet 4 Drive data_02 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3
#> Valiant data_02 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3
#> Merc 280 data_02 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4
#> Merc 280C data_02 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4
#> Ferrari Dino data_02 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5
#> carb
#> Datsun 710 1
#> Merc 240D 2
#> Merc 230 2
#> Fiat 128 1
#> Honda Civic 2
#> Toyota Corolla 1
#> Toyota Corona 1
#> Fiat X1-9 1
#> Porsche 914-2 2
#> Lotus Europa 2
#> Volvo 142E 2
#> Mazda RX4 4
#> Mazda RX4 Wag 4
#> Hornet 4 Drive 1
#> Valiant 1
#> Merc 280 4
#> Merc 280C 4
#> Ferrari Dino 6
bind_union(spl[[1L]], spl[[2L]], spl[[3L]])
#> data mpg cyl disp hp drat wt qsec vs am
#> Datsun 710 data_01 22.8 4 108.0 93 3.85 2.320 18.61 1 1
#> Merc 240D data_01 24.4 4 146.7 62 3.69 3.190 20.00 1 0
#> Merc 230 data_01 22.8 4 140.8 95 3.92 3.150 22.90 1 0
#> Fiat 128 data_01 32.4 4 78.7 66 4.08 2.200 19.47 1 1
#> Honda Civic data_01 30.4 4 75.7 52 4.93 1.615 18.52 1 1
#> Toyota Corolla data_01 33.9 4 71.1 65 4.22 1.835 19.90 1 1
#> Toyota Corona data_01 21.5 4 120.1 97 3.70 2.465 20.01 1 0
#> Fiat X1-9 data_01 27.3 4 79.0 66 4.08 1.935 18.90 1 1
#> Porsche 914-2 data_01 26.0 4 120.3 91 4.43 2.140 16.70 0 1
#> Lotus Europa data_01 30.4 4 95.1 113 3.77 1.513 16.90 1 1
#> Volvo 142E data_01 21.4 4 121.0 109 4.11 2.780 18.60 1 1
#> Mazda RX4 data_02 21.0 6 160.0 110 3.90 2.620 16.46 0 1
#> Mazda RX4 Wag data_02 21.0 6 160.0 110 3.90 2.875 17.02 0 1
#> Hornet 4 Drive data_02 21.4 6 258.0 110 3.08 3.215 19.44 1 0
#> Valiant data_02 18.1 6 225.0 105 2.76 3.460 20.22 1 0
#> Merc 280 data_02 19.2 6 167.6 123 3.92 3.440 18.30 1 0
#> Merc 280C data_02 17.8 6 167.6 123 3.92 3.440 18.90 1 0
#> Ferrari Dino data_02 19.7 6 145.0 175 3.62 2.770 15.50 0 1
#> Hornet Sportabout data_03 18.7 8 360.0 175 3.15 3.440 17.02 0 0
#> Duster 360 data_03 14.3 8 360.0 245 3.21 3.570 15.84 0 0
#> Merc 450SE data_03 16.4 8 275.8 180 3.07 4.070 17.40 0 0
#> Merc 450SL data_03 17.3 8 275.8 180 3.07 3.730 17.60 0 0
#> Merc 450SLC data_03 15.2 8 275.8 180 3.07 3.780 18.00 0 0
#> Cadillac Fleetwood data_03 10.4 8 472.0 205 2.93 5.250 17.98 0 0
#> Lincoln Continental data_03 10.4 8 460.0 215 3.00 5.424 17.82 0 0
#> Chrysler Imperial data_03 14.7 8 440.0 230 3.23 5.345 17.42 0 0
#> Dodge Challenger data_03 15.5 8 318.0 150 2.76 3.520 16.87 0 0
#> AMC Javelin data_03 15.2 8 304.0 150 3.15 3.435 17.30 0 0
#> Camaro Z28 data_03 13.3 8 350.0 245 3.73 3.840 15.41 0 0
#> Pontiac Firebird data_03 19.2 8 400.0 175 3.08 3.845 17.05 0 0
#> Ford Pantera L data_03 15.8 8 351.0 264 4.22 3.170 14.50 0 1
#> Maserati Bora data_03 15.0 8 301.0 335 3.54 3.570 14.60 0 1
#> gear carb
#> Datsun 710 4 1
#> Merc 240D 4 2
#> Merc 230 4 2
#> Fiat 128 4 1
#> Honda Civic 4 2
#> Toyota Corolla 4 1
#> Toyota Corona 3 1
#> Fiat X1-9 4 1
#> Porsche 914-2 5 2
#> Lotus Europa 5 2
#> Volvo 142E 4 2
#> Mazda RX4 4 4
#> Mazda RX4 Wag 4 4
#> Hornet 4 Drive 3 1
#> Valiant 3 1
#> Merc 280 4 4
#> Merc 280C 4 4
#> Ferrari Dino 5 6
#> Hornet Sportabout 3 2
#> Duster 360 3 4
#> Merc 450SE 3 3
#> Merc 450SL 3 3
#> Merc 450SLC 3 3
#> Cadillac Fleetwood 3 4
#> Lincoln Continental 3 4
#> Chrysler Imperial 3 4
#> Dodge Challenger 3 2
#> AMC Javelin 3 2
#> Camaro Z28 3 4
#> Pontiac Firebird 3 2
#> Ford Pantera L 5 4
#> Maserati Bora 5 8