r - 避免过多的滑块输入

Question

我对闪亮有点陌生，但在 R 方面有经验。

简而言之，我有一个闪亮的应用程序，它目前实现了 20 个滑块输入，但这让 UI 看起来又脏又乱。我已经探索过用 div() 包装输入语句来调整高度，但后来我松开了滑块的标签。我也尝试过其他输入，但我正在寻找更有说服力的东西。

我记得有人很了解闪亮的讨论覆盖地图的少量输入，但我没有运气在网上找到任何东西。有人能指出我合适的资源吗？

下面是我的代码。我知道在某些情况下我可以使用一些响应式函数并进行一些一般性的整理，但我稍后会进行这些调整。

ui <- fluidPage(

titlePanel(h2('Weather Application', align = 'center' )),

sidebarLayout(

sidebarPanel(

  selectInput(inputId = 'fiscalmonth', 
              label = 'Select a month', 
              choices = c(1:12), 
              selected = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'ames', 
              label = 'AMES', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'atlanta', 
              label = 'ATLANTA', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'bangor', 
              label = 'BANGOR', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'bozeman', 
              label = 'BOZEMAN', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'columbus', 
              label = 'COLUMBUS', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'dallas', 
              label = 'DALLAS', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'denver', 
              label = 'DENVER', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'houston', 
              label = 'HOUSTON', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'lansing', 
              label = 'LANSING', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'losangeles', 
              label = 'LOS ANGELES', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'madison', 
              label = 'MADISON', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'memphis', 
              label = 'MEMPHIS', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'miami',
              label = 'MIAMI',
              min = 0, 
              max = 100, 
              value = 100, 
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'minneapolis', 
              label = 'MINNEAPOLIS', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'peoria', 
              label = 'PEORIA', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'pittsburgh', 
              label = 'PITTSBURGH', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'richmond', 
              label = 'RICHMOND', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'sacramento', 
              label = 'SACRAMENTO', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'seattle', 
              label = 'SEATTLE', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1),

  #adding widgit for user to set individual city weight
  sliderInput(inputId = 'syracuse', 
              label = 'SYRACUSE', 
              min = 0, 
              max = 100, 
              value = 100,
              step = 1)
),

mainPanel(

  plotOutput('map', height = 800),

  plotOutput('scatter', height = 800)

)

)
)

server <- function(input, output){

output$map <- renderPlot({

country <- map_data('usa')

country %>% ggplot(aes(long, lat)) +
  geom_path(aes(group = group)) +
  geom_point(aes(Long, Lat),
             size = input$ames/7, colour = 'green', alpha = .15, 
             data = ctycord %>% filter(City == 'Ames')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Ames')) +
  geom_point(aes(Long, Lat), 
             size = input$atlanta/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Atlanta')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Atlanta')) +
  geom_point(aes(Long, Lat), 
             size = input$bangor/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Bangor')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Bangor')) +
  geom_point(aes(Long, Lat), 
             size = input$bozeman/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Bozeman')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Bozeman')) +
  geom_point(aes(Long, Lat), 
             size = input$columbus/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Columbus')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Columbus')) +
  geom_point(aes(Long, Lat), 
             size = input$dallas/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Dallas')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Dallas')) +
  geom_point(aes(Long, Lat), 
             size = input$denver/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Denver')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Denver')) +
  geom_point(aes(Long, Lat), 
             size = input$houston/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Houston')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Houston')) +
  geom_point(aes(Long, Lat), 
             size = input$lansing/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Lansing')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Lansing')) +
  geom_point(aes(Long, Lat), 
             size = input$losangeles/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Los Angeles')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Los Angeles')) +
  geom_point(aes(Long, Lat), 
             size = input$madison/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Madison')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Madison')) +
  geom_point(aes(Long, Lat), 
             size = input$memphis/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Memphis')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Memphis')) +
  geom_point(aes(Long, Lat),
             size = input$miami/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Miami')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Miami')) +
  geom_point(aes(Long, Lat), 
             size = input$minneapolis/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Minneapolis')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Minneapolis')) +
  geom_point(aes(Long, Lat), 
             size = input$peoria/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Peoria')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Peoria')) +
  geom_point(aes(Long, Lat), 
             size = input$pittsburgh/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Pittsburgh')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Pittsburgh')) +
  geom_point(aes(Long, Lat), 
             size = input$richmond/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Richmond')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Richmond'), hjust = 1.5) +
  geom_point(aes(Long, Lat), 
             size = input$sacramento/7, colour = 'green', alpha = .15,
             data = ctycord %>% filter(City == 'Sacramento')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Sacramento'), hjust = -0.5) +
  geom_point(aes(Long, Lat), 
             size = input$seattle/7, colour = 'green', alpha = .19,
             data = ctycord %>% filter(City == 'Seattle')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Seattle'), hjust = -0.6) +
  geom_point(aes(Long, Lat),
             size = input$syracuse/7, colour = 'green', alpha = .19,
             data = ctycord %>% filter(City == 'Syracuse')) +
  geom_text(aes(Long, Lat, label = City), data = ctycord %>% filter(City == 'Syracuse'), hjust = -0.5) +
  theme_void()

})

}

shinyApp(ui=ui, server=server)

标签： rshinyslider