The goal of flipR is aid the user in inverting and flipping data frames. This includes flipping rows and columns, inverting the order of rows, and inverting the order of columns. Included is an example dataset.
Installation
You can install the released version of flipR from Github with:
devtools::install_github("fieldima/flipR", ref = "0.2.0")Example
This is a basic example of when you would use flipR:
library(flipR)
#Packaged with flipR is a set of simulation data that needs to be flipped.
sim <- simulation_data
#To flip the rows and columns, simply use flip()
flip(sim)
#> m.sig c.var s.var s.asr s.hgt d.cdf
#> 1 0.9290709 0.1758242 0.89110889 0.57742258 0.3716284 0.8831169
#> 2 0.9450549 0.7552448 0.35564436 0.08791209 0.3956044 0.8711289
#> 3 0.8791209 0.9210789 0.43356643 0.63936064 0.4695305 0.9790210
#> 4 0.9050949 0.8991009 0.02797203 0.48551449 0.5794206 0.8911089
#> 5 0.9330669 0.5694306 0.81318681 0.55744256 0.9470529 0.8491508
#This package also gives the user the ability to invert the order of rows or columns
invert_row(sim)
#> 1 2 3 4 5
#> d.cdf 0.8831169 0.87112887 0.9790210 0.89110889 0.8491508
#> s.hgt 0.3716284 0.39560440 0.4695305 0.57942058 0.9470529
#> s.asr 0.5774226 0.08791209 0.6393606 0.48551449 0.5574426
#> s.var 0.8911089 0.35564436 0.4335664 0.02797203 0.8131868
#> c.var 0.1758242 0.75524476 0.9210789 0.89910090 0.5694306
#> m.sig 0.9290709 0.94505495 0.8791209 0.90509491 0.9330669
invert_col(sim)
#> 5 4 3 2 1
#> m.sig 0.9330669 0.90509491 0.8791209 0.94505495 0.9290709
#> c.var 0.5694306 0.89910090 0.9210789 0.75524476 0.1758242
#> s.var 0.8131868 0.02797203 0.4335664 0.35564436 0.8911089
#> s.asr 0.5574426 0.48551449 0.6393606 0.08791209 0.5774226
#> s.hgt 0.9470529 0.57942058 0.4695305 0.39560440 0.3716284
#> d.cdf 0.8491508 0.89110889 0.9790210 0.87112887 0.8831169
#Finally, all functions in this package can output data in the form of data frames, tibbles, or data tables
flip(sim, "TB")
#> # A tibble: 5 x 6
#> m.sig c.var s.var s.asr s.hgt d.cdf
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 0.929 0.176 0.891 0.577 0.372 0.883
#> 2 0.945 0.755 0.356 0.0879 0.396 0.871
#> 3 0.879 0.921 0.434 0.639 0.470 0.979
#> 4 0.905 0.899 0.0280 0.486 0.579 0.891
#> 5 0.933 0.569 0.813 0.557 0.947 0.849
flip(sim, "DT")
#> m.sig c.var s.var s.asr s.hgt d.cdf
#> 1: 0.9290709 0.1758242 0.89110889 0.57742258 0.3716284 0.8831169
#> 2: 0.9450549 0.7552448 0.35564436 0.08791209 0.3956044 0.8711289
#> 3: 0.8791209 0.9210789 0.43356643 0.63936064 0.4695305 0.9790210
#> 4: 0.9050949 0.8991009 0.02797203 0.48551449 0.5794206 0.8911089
#> 5: 0.9330669 0.5694306 0.81318681 0.55744256 0.9470529 0.8491508
invert_row(sim, "DF")
#> 1 2 3 4 5
#> d.cdf 0.8831169 0.87112887 0.9790210 0.89110889 0.8491508
#> s.hgt 0.3716284 0.39560440 0.4695305 0.57942058 0.9470529
#> s.asr 0.5774226 0.08791209 0.6393606 0.48551449 0.5574426
#> s.var 0.8911089 0.35564436 0.4335664 0.02797203 0.8131868
#> c.var 0.1758242 0.75524476 0.9210789 0.89910090 0.5694306
#> m.sig 0.9290709 0.94505495 0.8791209 0.90509491 0.9330669
invert_row(sim, "TB")
#> # A tibble: 6 x 5
#> `1` `2` `3` `4` `5`
#> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 0.883 0.871 0.979 0.891 0.849
#> 2 0.372 0.396 0.470 0.579 0.947
#> 3 0.577 0.0879 0.639 0.486 0.557
#> 4 0.891 0.356 0.434 0.0280 0.813
#> 5 0.176 0.755 0.921 0.899 0.569
#> 6 0.929 0.945 0.879 0.905 0.933
invert_col(sim, "DT")
#> 5 4 3 2 1
#> 1: 0.9330669 0.90509491 0.8791209 0.94505495 0.9290709
#> 2: 0.5694306 0.89910090 0.9210789 0.75524476 0.1758242
#> 3: 0.8131868 0.02797203 0.4335664 0.35564436 0.8911089
#> 4: 0.5574426 0.48551449 0.6393606 0.08791209 0.5774226
#> 5: 0.9470529 0.57942058 0.4695305 0.39560440 0.3716284
#> 6: 0.8491508 0.89110889 0.9790210 0.87112887 0.8831169