6 mapdims()
The function mapdims() calls apply() to map over a dataset’s dimensions, saving the column- and row-wise results separately in a list.
The required inputs for these functions are f and x, respectively the function to execute and the dataset over which to perform the function. The output is a list of arrays (typically a vector or matrix, depending on the function being passed).
6.0.1 Mapping dimensions
## $rowwise
## Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
## 4.000 4.000 4.000 3.215
## Hornet Sportabout Valiant Duster 360 Merc 240D
## 3.440 3.460 4.000 4.000
## Merc 230 Merc 280 Merc 280C Merc 450SE
## 4.000 4.000 4.000 4.070
## Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
## 3.730 3.780 5.250 5.424
## Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla
## 5.345 4.000 4.000 4.000
## Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
## 3.700 3.520 3.435 4.000
## Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
## 3.845 4.000 4.430 4.000
## Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E
## 5.000 6.000 8.000 4.000
##
## $colwise
## mpg cyl disp hp drat wt qsec vs am gear
## 19.200 6.000 196.300 123.000 3.695 3.325 17.710 0.000 0.000 4.000
## carb
## 2.0006.1 mapc() and mapr()
To apply a function column-wise in R, apply(x, 2, f) can be called–for row-wise results, the margin input (i.e., the second input) can be set to 1. For situational convenience, the functions mapc() and mapr() achieve the same results, respectively.
The required inputs for these functions are f and x, respectively the function to execute and the dataset over which to perform the function. The output is an array (typically a vector or matrix, depending on the function being passed).
6.1.1 mapc/r()
## mpg cyl disp hp drat wt qsec vs am gear
## 19.200 6.000 196.300 123.000 3.695 3.325 17.710 0.000 0.000 4.000
## carb
## 2.000## Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
## 4.000 4.000 4.000 3.215
## Hornet Sportabout Valiant Duster 360 Merc 240D
## 3.440 3.460 4.000 4.000
## Merc 230 Merc 280 Merc 280C Merc 450SE
## 4.000 4.000 4.000 4.070
## Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
## 3.730 3.780 5.250 5.424
## Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla
## 5.345 4.000 4.000 4.000
## Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
## 3.700 3.520 3.435 4.000
## Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
## 3.845 4.000 4.430 4.000
## Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E
## 5.000 6.000 8.000 4.000