这是一个工作模板:
require(data.table)
require(shiny)
require(ggplot2)
x <- data.table(v1 = sample(letters[1:5], 100, replace = T),
v2 = sample(letters[1:2], 100, replace = T),
v3 = runif(100, 0, 1))
ui <- fluidPage(
sidebarPanel(
selectInput("in1", "Choice v1", selected = "All", choices = c("All" = list(letters[1:5]))),
selectInput("in2", "Choice v2", selected = "a", choices = letters[1:2])
),
mainPanel(
plotOutput("out1")
)
)
server <- function(input, output){
output$out1 <- renderPlot({
ggplot(x[v1 %in% input$in1 & v2 %in% input$in2], aes(x = v3)) +
geom_density(fill = "dodgerblue4", alpha = .7) +
theme_light()
})
}
runApp(shinyApp(ui, server))
这里的问题是我想允许在变量中选择值的子集。行selectInput("in1", "Choice v1", selected = "All", choices = c("All" = list(letters[1:5])))
旨在将letters[1:5]
传递给input$in1
,有效地选择所有值并在v1
上不执行数据子集化。
同样适用于任何其他值的子集,例如选择"a_b_c" = c("a", "b", "c")
或"All" = x[,unique(v1)]
等等。闪亮的是,它包含在其中的所有值的分解列表,基本上与期望的结果相反。
我知道有selectizeInput()
来选择多个值。但是,如果我希望所有变量都为selected = "All"
作为初始状态,那么这是不可行的。
答案 0 :(得分:3)
这样的事情会起作用吗?
#rm(list=ls())
require(data.table)
require(shiny)
require(ggplot2)
x <- data.table(v1 = sample(letters[1:5], 100, replace = T),
v2 = sample(letters[1:2], 100, replace = T),
v3 = runif(100, 0, 1))
ui <- fluidPage(
sidebarPanel(
selectInput("in1", "Choice v1", selected = "All", choices = c("All",letters[1:5])),
selectInput("in2", "Choice v2", selected = "a", choices = letters[1:2])
),
mainPanel(
plotOutput("out1")
)
)
server <- function(input, output){
output$out1 <- renderPlot({
value <- input$in1
if(value == "All"){
value <- letters[1:5]
}
ggplot(x[v1 %in% value & v2 %in% input$in2], aes(x = v3)) +
geom_density(fill = "dodgerblue4", alpha = .7) +
theme_light()
})
}
runApp(shinyApp(ui, server))
答案 1 :(得分:0)
shiny
支持在selectInput
中选择多个值。您需要设置multiple = TRUE
和selectize = FALSE
。我认为这将为您提供您想要的功能。
然后,您可以使choices
和selected
变量相同,以预先选择所有变量。如果您需要使用“全部”功能,则需要添加操作按钮才能运行updateSelectInput
。可以通过编写模块来完成这两个功能的组合。
require(data.table)
require(shiny)
require(ggplot2)
x <- data.table(v1 = sample(letters[1:5], 100, replace = T),
v2 = sample(letters[1:2], 100, replace = T),
v3 = runif(100, 0, 1))
ui <- fluidPage(
sidebarPanel(
selectInput("in1", "Choice v1",
selected = letters[1:5],
choices = letters[1:5],
multiple = TRUE,
selectize = FALSE),
selectInput("in2", "Choice v2",
selected = letters[1:2],
choices = letters[1:2],
multiple = TRUE,
selectize = FALSE)
),
mainPanel(
plotOutput("out1")
)
)
server <- function(input, output){
output$out1 <- renderPlot({
ggplot(x[v1 %in% input$in1 & v2 %in% input$in2], aes(x = v3)) +
geom_density(fill = "dodgerblue4", alpha = .7) +
theme_light()
})
}
runApp(shinyApp(ui, server))
答案 2 :(得分:0)
在阅读其他答案并想知道可能的清洁和紧凑的解决方法时,这就是我想出的。采用干净的方法来添加新变量至关重要。
require(data.table)
require(shiny)
require(ggplot2)
x <- data.table(v1 = sample(letters[1:5], 100, replace = T),
v2 = sample(letters[1:2], 100, replace = T),
v3 = runif(100, 0, 1))
map.dt <- function(x, variables){
map.out <- data.table(name = character(), variable = character(), value = character())
for(i in variables){
map.out <- rbind(map.out,
data.table(name = x[,sort(as.character(na.omit(unique(get(i)))))],
variable = i,
value = x[,sort(as.character(na.omit(unique(get(i)))))]),
data.table(name = "All",
variable = i,
value = x[,sort(as.character(na.omit(unique(get(i)))))]))
}
return(map.out)
}
y <- map.dt(x, c("v1", "v2"))
ui <- fluidPage(
sidebarPanel(
selectInput("in1", "Choice v1", selected = "All", choices = c("All", letters[1:5])),
selectInput("in2", "Choice v2", selected = "All", choices = c("All", letters[1:2]))
),
mainPanel(
plotOutput("out1")
)
)
server <- function(input, output){
output$out1 <- renderPlot({
ggplot(x[v1 %in% y[variable == "v1" & name == input$in1, value] &
v2 %in% y[variable == "v2" & name == input$in2, value]],
aes(x = v3)) +
geom_density(fill = "dodgerblue4", alpha = .7) +
theme_light()
})
}
runApp(shinyApp(ui, server))
基本上,它正在添加一个通过函数生成的中间映射表。