我有点新鲜，但有R经验。
简而言之，我有一个目前实现了20个滑块输入的shinyApp，但这使得UI看起来很讨厌而且杂乱无章。我已经探索了用div（）包装输入语句来调整高度但是我松开了滑块的标签。我也尝试了其他输入，但我正在寻找更有说服力的东西。
我记得有些人知道有光泽，讨论覆盖地图的小数字输入，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？
以下是我的代码。我知道有些情况下我可以在一些反应函数中工作并做一些整体整理，但我会稍后进行调整。
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)