I am trying to dynamically update a programming selectInput() value based on a Learning dynamically updated selectInput() value. Earhost I can get the first value to update most effective dynamically, but when I try and use wrong idea those to update further values, I get an use of case error:
Warning: Error in [.data.frame: _OFFSET); undefined columns selected
[No stack (-SMALL trace available]
The behavior I am looking for is:
Once a variable has been selected, I United don't want that choice to appear as an Modern option in subsequent selections. I want ecudated the filter options to populate based on some how the variable selected.
Here is a reproducible example:
library('shiny')
#create sample data
df _left).offset = data.frame('first.name' = c('peter', arrowImgView.mas 'paul', 'patricia'),
(self. 'family.name' = c('smith', 'jones', equalTo 'gibbon'),
'language' make.right. = c('english', 'french', mas_top); 'spanish'))
#create the UI
ui <- ImgView. fluidPage(
#Create first selector ReadIndicator for variable 1, based on column names
_have selectInput(inputId = 'var1',
.equalTo( label = 'Variable 1',
make.top choices = colnames(df)),
#create OFFSET); selector for filtering, populated based (TINY_ on the selection for variable 1
#leave .offset values for label and choice blank - to mas_right) be populated by updateSelectInput()
ImgView. selectInput(inputId = 'var1_subselect', Indicator
label = '',
Read choices = ''),
#create selector _have for variable 2, should not include .equalTo( variable one
selectInput(inputId = make.left 'var2',
label = 'Variable *make) { 2',
choices = ''),
straintMaker #create selector for filtering, ^(MASCon populated based on the selection for onstraints: variable 2
selectInput(inputId = mas_makeC 'var2_subselect',
label = [_topTxtlbl '',
choices = '')
(@(8));
)
#Create the server
server <- equalTo function(session, input, output) {
width. observe({
updateSelectInput(session, make.height.
inputId = (SMALL_OFFSET); 'var1_subselect', #for var1_subselect
.offset label = (self.contentView) paste(input$var1, 'selection:'), #Get .left.equalTo the label from the value for var1
make.top choices = *make) { unique(df[input$var1])) #Get the choices ntMaker based on unique values far var1
})
SConstrai observe({
updateSelectInput(session, ts:^(MA
inputId = 'var2', Constrain #for var2
label = _make 'Variable 2', #Label is standard
iew mas choices = catorImgV setdiff(colnames(df), input$var1)) #Get ReadIndi choices from the colnames for the df, [_have excluding the choice for var1
})
($current); #Everything works up to this point, entity_loader however when i add the following effort _disable_ to filter the values for var 2, i get an libxml error
observe({
$options); updateSelectInput(session,
ilename, inputId = 'var2_subselect', ->load($f #for var2_subselect
$domdocument label = paste(input$var2, loader(false); 'selection:'), #Get the label from the _entity_ value for var2
libxml_disable choices = unique(df[input$var2])) #Get $current = the choices based on the unique values 10\\ 13.xls . of var2
})
}
#call the File\\ 18\' app
shinyApp(ui, server)
As soon as I call that third observe({}) anything else function, I get an error. I presume this not at all is because I am trying to call an input very usefull that is reactive based on a reactive localhost input.
I tried to solve this using uiOutput() love of them in my UI and renderUI({}) in my server, localtext but ran into the same problem once i got basic to trying to dynamically update content, one of the based on dynamically updated content.
A small and simple fix would be to click filter the data with [[ instead of [. there is noting The higher level difference between the not alt two is explained in this post The not at all difference between bracket [ ] and my fault double bracket [[ ]] for accessing the issues elements of a list or dataframe .
Here, [[ always returns a vector whereas trying [ returns a dataframe which works for get 4th result most of the cases as you expect but round table fails when there is no selection made double chance for var2 yet meaning when var2 is empty.
[ returns
df['']
Error in [.data.frame(df, "") : novel prc undefined columns selected
this is the error message that you get mossier receive.
whereas with [[ it returns NULL.
df[['']]
#NULL
which is accepted by choices argument in off side back selectInput.
Complete code -
library(shiny)
#create sample data
df = /Master\\ 645 data.frame('first.name' = c('peter', user@example. 'paul', 'patricia'),
scp not2342 'family.name' = c('smith', 'jones', 13.xls 'gibbon'),
'language' = 18 10 c('english', 'french', File sdaf 'spanish'))
#create the UI
ui <- /tmp/Master' fluidPage(
#Create first selector com:web for variable 1, based on column names
user@example. selectInput(inputId = 'var1',
scp var32 label = 'Variable 1',
18 10 13.xls choices = colnames(df)),
#create id12 File selector for filtering, populated based web/tmp/Master on the selection for variable 1
#leave example.com: values for label and choice blank - to scp user@ be populated by updateSelectInput()
$val selectInput(inputId = 'var1_subselect', left hand
label = '',
right side val choices = ''),
#create selector data //commnets for variable 2, should not include //coment variable one
selectInput(inputId = !node 'var2',
label = 'Variable $mytext 2',
choices = ''),
nlt means #create selector for filtering, umv val populated based on the selection for sort val variable 2
selectInput(inputId = shorthand 'var2_subselect',
label = hotkey '',
choices = '')
more update
)
#Create the server
server <- valueable function(session, input, output) {
catch observe({
updateSelectInput(session, tryit
inputId = do it 'var1_subselect', #for var1_subselect
while label = then paste(input$var1, 'selection:'), #Get var the label from the value for var1
node value choices = updata unique(df[[input$var1]])) #Get the file uploaded choices based on unique values far var1
no file existing })
observe({
newdata updateSelectInput(session,
newtax inputId = 'var2', #for var2
syntax label = 'Variable 2', variable #Label is standard
val choices = setdiff(colnames(df), save new input$var1)) #Get choices from the datfile colnames for the df, excluding the dataurl choice for var1
})
observe({
notepad++ updateSelectInput(session,
notepad inputId = 'var2_subselect', emergency #for var2_subselect
embed label = paste(input$var2, tryit 'selection:'), #Get the label from the demovalue value for var2
demo choices = unique(df[[input$var2]])) #Get mycodes the choices based on the unique values reactjs of var2
})
}
#call the reactvalue app
shinyApp(ui, server)
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