我差不多完成了我的shinyapp，最后一部分是在我的server.R中添加一个下载按钮。我按照＆＃34;如何下载＆＃34;的说明进行操作。在Rshiny但它在我的案例中并没有真正起作用。
这是我的ui.R
library(shiny)
library(hurricaneexposure)
library(hurricaneexposuredata)
library(ggplot2)
data("hurr_tracks")
storms <- unique(hurr_tracks$storm_id)
storm_years <- as.numeric(gsub(".+-", "", storms))
storms <- storms[storm_years <= 2011]
years <- unique(storm_years)
years <- years[years <= 2011]
shinyUI(fluidPage(
# Application title
titlePanel("County-level exposure to tropical storms"),
sidebarLayout(
sidebarPanel(
selectInput("year", label = "Storm year", years,
selected = "1988"),
# This outputs the dynamic UI component
uiOutput("ui"),
selectInput("metric", label="Storm exposure metric:",
choices = c("distance", "rainfall", "wind"),
selected = "distance"),
numericInput("limit",
label = "Limit range",
value = 100),
downloadButton('downloadData', 'Download The Table')
),
mainPanel(plotOutput("map"))
),
fluidRow(
DT::dataTableOutput("table")
)
))
这是我的服务器.R
library(shiny)
library(devtools)
library(ggplot2)
library(hurricaneexposuredata)
library(hurricaneexposure)
library(choroplethrMaps)
library(dplyr)
data("hurr_tracks")
data("county_centers")
storms <- unique(hurr_tracks$storm_id)
storm_years <- as.numeric(gsub(".+-", "", storms))
storms <- storms[storm_years <= 2011]
years <- unique(storm_years)
years <- years[years <= 2011]
all_fips <- unique(county_centers$fips)
## Split storm_id based on same year
stm <- split(storms, gsub(".+-", "", storms))
stm <- lapply(stm, function (x) gsub("-.+", "", x))
shinyServer(function(input, output, session) {
output$ui <- renderUI({
selectInput("storm_name", label = "Storm name", stm[input$year],
selected = "Alberto")
})
output$map <-renderPlot({
storm_id <- paste(input$storm_name, input$year, sep = "-")
a <- map_counties(storm = storm_id, metric = input$metric)
map_tracks(storms = storm_id, plot_object = a, plot_points = FALSE) +
ggtitle(paste(input$storm_name, input$year, input$metric, sep = ", "))
})
output$table <- DT::renderDataTable(DT::datatable({
if(input$metric == "distance"){
tab_out <- county_distance(counties = all_fips, start_year = input$year,
end_year = input$year, dist_limit = input$limit) %>%
dplyr::filter(storm_id == paste(input$storm_name,
input$year, sep = "-")) %>%
dplyr::left_join(county_centers, by = "fips") %>%
dplyr::mutate(county = paste(county_name, state_name, sep = ", ")) %>%
dplyr::select(county, fips, closest_date, storm_dist) %>%
arrange(storm_dist)
} else if (input$metric == "rain"){
tab_out <- county_rain(counties = all_fips, start_year = input$year,
end_year = input$year, rain_limit = input$limit) %>%
dplyr::filter(storm_id == paste(input$storm_name,
input$year, sep = "-")) %>%
dplyr::left_join(county_centers, by = "fips") %>%
dplyr::mutate(county = paste(county_name, state_name, sep = ", ")) %>%
dplyr::select(county, fips, closest_date, tot_precip) %>%
dplyr::rename(rainfall_mm = tot_precip) %>%
arrange(desc(rainfall_mm))
} else if(input$metric == "wind"){
tab_out <- county_wind(counties = all_fips, start_year = input$year,
end_year = input$year, wind_limit = input$limit) %>%
dplyr::filter(storm_id == paste(input$storm_name,
input$year, sep = "-")) %>%
dplyr::left_join(county_centers, by = "fips") %>%
dplyr::mutate(county = paste(county_name, state_name, sep = ", ")) %>%
dplyr::select(county, fips, max_sust) %>%
dplyr::rename(wind_mps = max_sust) %>%
arrange(desc(wind_mps))
}
})
)
output$downloadData <- downloadHandler(
#filename = function() { paste(input$storm_name, input$year, input$metric,'.csv', sep='_') },
filename = "ex.csv",
content = function(file) {
write.csv(tab_out, file)
}) ### if I can recall the table
})
代码看起来很长但我希望有人能成功运行它。这个应用程序的想法很简单，我只是想知道如何将我的输出（只是那个表）下载为csv格式