labelr-package
The goal of labelr is to make labelling data frames easier. Think of using different labels in ggplot2 because of different languages or because of a different audience. Or just because you want to keep things more dynamic.
Installation
You can install it like this (not on CRAN):
devtools::install_github("tinino/labelr")
Find the repo here: https://github.com/tinino/labelr
How to use labelr
Let’s take iris. We have Species as factor.
str(iris)
#> 'data.frame': 150 obs. of 5 variables:
#> $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
#> $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
#> $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
#> $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
#> $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
Now assume you want to change these values, i.e. give it a new label (maybe translate to different languages or whatever). Here, we want to change labels to titlecase. Define a data frame with a column named from and a column named to:
(species_from_to <- data.frame(
from = levels(iris$Species),
to = stringr::str_to_title(levels(iris$Species))
))
#> from to
#> 1 setosa Setosa
#> 2 versicolor Versicolor
#> 3 virginica Virginica
Now set the labels. For convencience, make sure your entry is named like the variable (attention: Species is titlecase!):
labelr::labels$set(Species = species_from_to)
Now label iris:
labelr::label_df(iris)[c(1:3, 51:53, 101:103), ]
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 Setosa
#> 2 4.9 3.0 1.4 0.2 Setosa
#> 3 4.7 3.2 1.3 0.2 Setosa
#> 51 7.0 3.2 4.7 1.4 Versicolor
#> 52 6.4 3.2 4.5 1.5 Versicolor
#> 53 6.9 3.1 4.9 1.5 Versicolor
#> 101 6.3 3.3 6.0 2.5 Virginica
#> 102 5.8 2.7 5.1 1.9 Virginica
#> 103 7.1 3.0 5.9 2.1 Virginica
Now immagine you want to be able to switch labels using other distinctive parameters, like language. Here, an example might be uppercase as a second representation. To achieve this, just add another column, for example casetype:
(species_from_to_titlecase <- data.frame(
from = levels(iris$Species),
to = stringr::str_to_title(levels(iris$Species)),
casetype = "titlecase"
))
#> from to casetype
#> 1 setosa Setosa titlecase
#> 2 versicolor Versicolor titlecase
#> 3 virginica Virginica titlecase
# set that (hence replace previous):
labelr::labels$set(Species = species_from_to_titlecase)
# and add uppercase:
(species_from_to_uppercase <- data.frame(
from = levels(iris$Species),
to = toupper(levels(iris$Species)),
casetype = "uppercase"
))
#> from to casetype
#> 1 setosa SETOSA uppercase
#> 2 versicolor VERSICOLOR uppercase
#> 3 virginica VIRGINICA uppercase
# append this (makes it also new default):
labelr::labels$append(Species = species_from_to_uppercase)
Now, default is uppercase:
labelr::label_df(iris)[c(1:3, 51:53, 101:103), ]
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 SETOSA
#> 2 4.9 3.0 1.4 0.2 SETOSA
#> 3 4.7 3.2 1.3 0.2 SETOSA
#> 51 7.0 3.2 4.7 1.4 VERSICOLOR
#> 52 6.4 3.2 4.5 1.5 VERSICOLOR
#> 53 6.9 3.1 4.9 1.5 VERSICOLOR
#> 101 6.3 3.3 6.0 2.5 VIRGINICA
#> 102 5.8 2.7 5.1 1.9 VIRGINICA
#> 103 7.1 3.0 5.9 2.1 VIRGINICA
But we can also ask for titlecase:
labelr::label_df(iris, casetype = "titlecase")[c(1:3, 51:53, 101:103), ]
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 Setosa
#> 2 4.9 3.0 1.4 0.2 Setosa
#> 3 4.7 3.2 1.3 0.2 Setosa
#> 51 7.0 3.2 4.7 1.4 Versicolor
#> 52 6.4 3.2 4.5 1.5 Versicolor
#> 53 6.9 3.1 4.9 1.5 Versicolor
#> 101 6.3 3.3 6.0 2.5 Virginica
#> 102 5.8 2.7 5.1 1.9 Virginica
#> 103 7.1 3.0 5.9 2.1 Virginica
Note, that the levels are still the same and will remain in the factor-order, if you specify it as a factor. If you however label a character value, it will return a factor according to the order you set in labels$set(). This is nice for use with, for example, ggplot2, where you might want to achieve a specific default order.
Leave a Comment