teal
apps with the filter panelThe filter panel is an integral part of all teal
applications and is included on the right side. Based on the selections
made in the filter panel, filter expressions are executed before passing
data to teal
modules. The technical details of the filter
panel are extensively described in teal.slice
documentation.
By default, init
initializes the filter panel without
any active filters but allows the user to add filters on any column. To
start a teal
application with predefined filters, one must
specify the filter
argument. In the following example four
filters are specified using the teal_slice
function and
wrapped together with teal_slices
.
library(teal)
app <- init(
data = teal_data(IRIS = iris, CARS = mtcars),
modules = example_module(),
filter = teal_slices(
teal_slice(dataname = "IRIS", varname = "Sepal.Length"),
teal_slice(dataname = "IRIS", varname = "Species", selected = "setosa"),
teal_slice(dataname = "CARS", varname = "mpg", selected = c(20, Inf)),
teal_slice(dataname = "CARS", expr = "qsec < 20", title = "1/4 mile under 20 sec", id = "qsec_20")
)
)
if (interactive()) {
shinyApp(app$ui, app$server)
}
teal.slice
teal_module
Each teal_module
(see ?module
) object
contains the datanames
attribute that determines which data
sets are to be sent to that module. The filter panel will display only
those data sets and hide the rest when this module is active.
library(teal)
app <- init(
data = teal_data(IRIS = iris, CARS = mtcars),
modules = modules(
example_module(label = "all datasets"),
example_module(label = "IRIS only", datanames = "IRIS"),
example_module(label = "CARS only", datanames = "CARS"),
example_module(label = "no filter panel", datanames = NULL)
)
)
if (interactive()) {
shinyApp(app$ui, app$server)
}
teal
contains the teal_slices
function that
extends the original teal_slices
found in
teal.slice
by adding two arguments:
module_specific
and mapping
. By default
init
initializes the app with a “global” filter panel,
where all modules use the same filters. Setting
module_specific = TRUE
switches to a “module-specific”
filter panel, where each module can have a different set of filters
active at any time. It is still possible to set global filters that will
be shared among modules.
One possible scenario is depicted in the figure below:
filter 1
is shared by all modulesfilter 2
is shared by module 1
and
module 3
filter 3
is used only by module 2
filter 4
is used only by module 1
filter 5
and filter 6
are not active in
any of the modulesTo achieve the described setup, one must set the
module_specific
argument to TRUE
and use the
mapping
argument to match filters to modules.
mapping
takes a named list where element names correspond
to module labels, and elements are vectors of teal_slice
id
s applied to that module at startup.
teal_slice
s listed the element called
"global_filters"
will be applied to all modules.
For a detailed explanation about the filter states, see this
teal.slice
vignette.
library(teal)
app <- init(
data = teal_data(mtcars = mtcars),
modules = modules(
example_module(label = "module 1"),
example_module(label = "module 2"),
example_module(label = "module 3"),
example_module(label = "module 4")
),
filter = teal_slices(
# filters created with id
teal_slice(dataname = "mtcars", varname = "mpg", id = "filter 1"),
teal_slice(dataname = "mtcars", varname = "cyl", id = "filter 2"),
teal_slice(dataname = "mtcars", varname = "disp", id = "filter 3"),
teal_slice(dataname = "mtcars", varname = "hp", id = "filter 4"),
teal_slice(dataname = "mtcars", varname = "drat", id = "filter 5"),
teal_slice(dataname = "mtcars", varname = "wt", id = "filter 6"),
# module-specific filtering enabled
module_specific = TRUE,
# filters mapped to modules
mapping = list(
"module 1" = c("filter 2", "filter 4"),
"module 2" = "filter 3",
"module 3" = "filter 2",
global_filters = "filter 1"
)
)
)
if (interactive()) {
shinyApp(app$ui, app$server)
}