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I have an shiny app that ask the user to upload a file (a tabulated file with data), then it renders this file into a table and the user can filter some values based on numericInput, selectInput, and textAreaInput. The user has to select the filters and then press a button in order to filter the table.
There is no sequential filtering, i.e, the user can fill all the filters or just one. Every time the user choose a filter the value of the other filters get updated (selectInput inputs) and this is the behaviour I want. However, once the Filter button is pressed, I can't see the previous selection and also I can't reset the filters.
What I would like to achieve is to maintain the actual behaviour when updating the filters, i.e, once I choose a filter and press the filter button the other selectInput choices are automatically updated, BUT I want to keep track of the filters choices, so the user can see the filters he/she has selected. That was what I was expecting but everytime I press the button Filter it seems that the filter tab is rendered again.
Here is my app,
library(shiny)
library(vroom)
library(dplyr)
library(shinycssloaders)
library(shinydashboard)
library(shinydashboardPlus)
library(tidyr)
header <- dashboardHeader()
sidebar <- dashboardSidebar(width = 450,
sidebarMenu(id="tabs",
menuItem("Filtros", tabName="filtros", icon = icon("bar-chart-o")),
uiOutput("filtros")
)
)
body <- dashboardBody(
tabItems(
tabItem(tabName="filtros",
fluidRow(
column(12,dataTableOutput("tabla_julio") %>% withSpinner(color="#0dc5c1"))
)
)
)
)
ui <- dashboardPagePlus(enable_preloader = TRUE, sidebar_fullCollapse = TRUE, header, sidebar, body)
server = function(input, output, session) {
#Create the choices for sample input
vals <- reactiveValues(data=NULL)
vals$data <- iris
output$filtros <- renderUI({
datos <- vals$data
conditionalPanel("input.tabs == 'filtros'",
tagList(
div(style="display: inline-block;vertical-align:top; width: 221px;",numericInput(inputId="Sepal.Length", label="Sepal.Length", value=NA, min = NA, max = NA, step = NA)),
div(
div(style="display: inline-block;vertical-align:top; width: 224px;", selectInput(inputId = "Species", label = "Species", width = "220", choices=unique(datos$Species),
selected = NULL, multiple = TRUE, selectize = TRUE, size = NULL))
)
),
actionButton("filtrar", "Filter")
)
})
# create reactiveValues
vals <- reactiveValues(data=NULL)
vals$data <- iris
# Filter data
observeEvent(input$filtrar, {
tib <- vals$data
if (!is.na(input$Sepal.Length)){
tib <- tib %>% dplyr::filter(!Sepal.Length >= input$Sepal.Length)
print(head(tib))
} else { tib <- tib }
# Filter
if (!is.null(input$Species)){
toMatch <- paste0("\\b", input$Species, "\\b")
matches <- unique(grep(paste(toMatch,collapse="|"), tib$Species, value=TRUE))
tib <- tib %>% dplyr::filter(Species %in% matches)
} else { tib <- tib}
tib -> vals$data
print(head(tib, n=15))
})
# Reactive function creating the DT output object
output$tabla_julio <- DT::renderDataTable({
DT::datatable(vals$data)
})
}
shinyApp(ui, server)
607
Another Update:
library(shiny)
library(vroom)
library(dplyr)
library(shinycssloaders)
library(shinydashboard)
library(shinydashboardPlus)
library(tidyr)
header <- dashboardHeader()
sidebar <- dashboardSidebar(width = 450,
sidebarMenu(id = "tabs",
menuItem(
"Filtros",
tabName = "filtros",
icon = icon("bar-chart-o")
),
uiOutput("filtros")
))
body <- dashboardBody(tabItems(tabItem(tabName = "filtros",
fluidRow(
column(12,
DT::dataTableOutput("tabla_julio") # %>% withSpinner(color = "#0dc5c1")
)
))))
ui <-
dashboardPagePlus(
enable_preloader = FALSE,
sidebar_fullCollapse = TRUE,
header,
sidebar,
body
)
server = function(input, output, session) {
# Create the choices for sample input
vals <- reactiveValues(data = iris, filtered_data = iris)
output$filtros <- renderUI({
datos <- isolate(vals$data)
conditionalPanel(
"input.tabs == 'filtros'",
tagList(
div(
style = "display: inline-block;vertical-align:top; width: 221px;",
numericInput(
inputId = "SepalLength",
label = "Sepal.Length",
value = NA,
min = NA,
max = NA,
step = NA
)
),
div(
div(
style = "display: inline-block;vertical-align:top; width: 224px;",
selectInput(
inputId = "Species",
label = "Species",
width = "220",
choices = unique(isolate(datos$Species)),
selected = NULL,
multiple = TRUE,
selectize = TRUE,
size = NULL
)
)
)
),
actionButton("filtrar", "Filter", style = "width: 100px;"),
actionButton("reset", "Reset", style = "width: 100px;")
)
})
# Filter data
observeEvent(input$filtrar, {
tib <- vals$data
if (!is.na(input$SepalLength)) {
tib <- tib %>% dplyr::filter(Sepal.Length < input$SepalLength)
print(head(tib))
} else {
tib
}
# Filter
if (!is.null(input$Species)) {
tib <- tib %>% dplyr::filter(Species %in% input$Species)
} else {
tib
}
print(head(tib, n = 15))
vals$filtered_data <- tib
updateSelectInput(session, inputId = "Species", selected = input$Species, choices = unique(vals$filtered_data$Species))
})
observeEvent(input$reset, {
updateNumericInput(session, inputId = "SepalLength", value = NA)
updateSelectInput(session, inputId = "Species", selected = "")
})
# Reactive function creating the DT output object
output$tabla_julio <- DT::renderDataTable({
DT::datatable(vals$filtered_data)
}, server = FALSE)
}
shinyApp(ui, server)
Update: Here is what I think you are after. The most important step is to isolate the inputs in renderUI so they aren't re-rendered on every input change.
library(shiny)
library(vroom)
library(dplyr)
library(shinycssloaders)
library(shinydashboard)
library(shinydashboardPlus)
library(tidyr)
header <- dashboardHeader()
sidebar <- dashboardSidebar(width = 450,
sidebarMenu(id = "tabs",
menuItem(
"Filtros",
tabName = "filtros",
icon = icon("bar-chart-o")
),
uiOutput("filtros")
))
body <- dashboardBody(tabItems(tabItem(tabName = "filtros",
fluidRow(
column(12,
DT::dataTableOutput("tabla_julio") # %>% withSpinner(color = "#0dc5c1")
)
))))
ui <-
dashboardPagePlus(
enable_preloader = FALSE,
sidebar_fullCollapse = TRUE,
header,
sidebar,
body
)
server = function(input, output, session) {
# Create the choices for sample input
vals <- reactiveValues(data = iris, filtered_data = iris)
output$filtros <- renderUI({
datos <- isolate(vals$data)
conditionalPanel(
"input.tabs == 'filtros'",
tagList(
div(
style = "display: inline-block;vertical-align:top; width: 221px;",
numericInput(
inputId = "SepalLength",
label = "Sepal.Length",
value = NA,
min = NA,
max = NA,
step = NA
)
),
div(
div(
style = "display: inline-block;vertical-align:top; width: 224px;",
selectInput(
inputId = "Species",
label = "Species",
width = "220",
choices = unique(isolate(datos$Species)),
selected = NULL,
multiple = TRUE,
selectize = TRUE,
size = NULL
)
)
)
),
actionButton("filtrar", "Filter", style = "width: 100px;"),
actionButton("reset", "Reset", style = "width: 100px;")
)
})
# Filter data
observeEvent(input$filtrar, {
tib <- vals$data
if (!is.na(input$SepalLength)) {
tib <- tib %>% dplyr::filter(Sepal.Length < input$SepalLength)
print(head(tib))
} else {
tib
}
# Filter
if (!is.null(input$Species)) {
tib <- tib %>% dplyr::filter(Species %in% input$Species)
} else {
tib
}
print(head(tib, n = 15))
vals$filtered_data <- tib
})
observeEvent(input$reset, {
updateNumericInput(session, inputId = "SepalLength", value = NA)
updateSelectInput(session, inputId = "Species", selected = "")
})
# Reactive function creating the DT output object
output$tabla_julio <- DT::renderDataTable({
DT::datatable(vals$filtered_data)
}, server = FALSE)
}
shinyApp(ui, server)
Initial answer:
I'd recommend using the selectizeGroup-module from library(shinyWidgets).
It creates a
Group of mutually dependent
selectizeInputfor filtering data.frame's columns (like in Excel).
Besides the fact, that it only uses selectizeInput it seems to meet your requirements and saves us from a lot of typing.
Here is an example using the iris dataset:
library(shiny)
library(DT)
library(shinyWidgets)
library(datasets)
DF <- iris
names(DF) <- gsub("\\.", "", names(DF))
ui <- fluidPage(
fluidRow(
column(width = 10, offset = 1, tags$h3("Filter data with selectize group")),
column(width = 3, offset = 1,
selectizeGroupUI(
id = "my-filters",
params = list(
SepalLength = list(inputId = "SepalLength", title = "SepalLength:"),
SepalWidth = list(inputId = "SepalWidth", title = "SepalWidth:"),
PetalLength = list(inputId = "PetalLength", title = "PetalLength:"),
PetalWidth = list(inputId = "PetalWidth", title = "PetalWidth:"),
species = list(inputId = "Species", title = "Species:")
),
inline = FALSE
)),
column(
width = 10, offset = 1,DT::dataTableOutput(outputId = "table")
)
)
)
server <- function(input, output, session) {
filtered_table <- callModule(
module = selectizeGroupServer,
id = "my-filters",
data = DF,
vars = names(DF)
)
output$table <- DT::renderDataTable(filtered_table())
}
shinyApp(ui, server)
107
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