Appifyr offers three types of inputs: dropdown, text and number. Test
All input types share the arguments label and width. The label will be displayed next to the input on the form. The width argument accepts integer values between 1 and 12 (it’s using the bootstrap grid system). A value of 12 will make the input take an entire row. The default width is 4.
The inps argument takes a list where every element is named corresponding to one of the arguments to your function. So, for a function my_function(x, y) you must specify both x and y in the list, e.g. list(x = inp_text(), y = inp_text()). The names must match exactly. Note that it is possible to pass anything to ....
The text input inp_text is the most basic type of input.
appify("text_to_title", inps = list(plot_title = inp_text(width = 12)))You can use the number input inp_number type to restrict values to numbers.
appify("number_to_sample", inps = list(n = inp_number(from = 0, to = 10e9)))Appifyr’s function inp_dropdown accepts atomics, lists and datafarmes as arguments. Intrnally, appifyr always converts to a dataframe.
When given a vector as the first argument the keys will be equal to the values passed to the function.
appify("dropdown_to_filter",
inps = list(flower = inp_dropdown(unique(iris$Species))))A list should be used when one deals with a fairly small number of levels and needs specific names for those. The format is intuitive: list(key1 = "value1", key2 = "value2").
flowers <- list(
Setosa = "setosa",
Versicolor = "versicolor",
Virginica = "virginica"
)
appify("dropdown_to_filter", inps = list(flower = inp_dropdown(flowers)))The dataframe argument needs a specific format. There must be exactly two columns key and value. This type of passing the levels is most useful when one wants to create a large number of levels.
flowers <- data.frame(value = unique(iris$Species)) %>%
mutate(key = str_to_title(value))
appify("dropdown_to_filter", inps = list(flower = inp_dropdown(flowers)))