The goal of foofactor is to practice in the development of an R package. Functions include:
fbind()
freq_out()
should_factor_be_factor()
You can try out the dev version from GitHub with:
# install.packages("devtools")
devtools::install_github("csiu/foofactor")
We first load the package
library(foofactor)
In the package, I have also provided example factors
exampleFactor1
#> [1] setosa versicolor virginica
#> Levels: setosa versicolor virginica
exampleFactor2
#> [1] ctrl trt1 trt2
#> Levels: ctrl trt1 trt2
exampleFactor3
#> [1] setosa setosa setosa setosa setosa setosa
#> [7] setosa setosa setosa setosa versicolor versicolor
#> [13] versicolor versicolor versicolor versicolor versicolor versicolor
#> [19] versicolor versicolor versicolor versicolor versicolor versicolor
#> [25] versicolor virginica virginica virginica virginica virginica
#> [31] virginica virginica virginica virginica
#> Levels: setosa versicolor virginica
fbind
- Bind two factors togetherfbind(exampleFactor1, exampleFactor2, level.as.appears = TRUE)
#> [1] setosa versicolor virginica ctrl trt1 trt2
#> Levels: setosa versicolor virginica ctrl trt1 trt2
Here we bind together two factors. When we specify level.as.appears = FALSE
, the order of the levels will seemingly be random.
freq_out
- Create a frequency table for a factorfreq_out(exampleFactor3, n.sort = "descending")
#> Source: local data frame [3 x 2]
#>
#> x n
#> (fctr) (int)
#> 1 versicolor 15
#> 2 setosa 10
#> 3 virginica 9
n.sort
can take the values of ascending
, descending
, or NULL
(where NULL
refers to the default behaviour without sorting on the frequency column).
should_factor_stay_factor
- Should factor stay as factor?should_factor_stay_factor(exampleFactor3)
#> [1] TRUE
Here we ask whether it makes sense for a factor to stay as a factor e.g. if the number of unique values of a factor is equal to the length, then maybe the factor would be better suited as a character vector.
For more information, please check out the vignette at:
vignette("foofactor", package = "foofactor")
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