我是新手，并编写了我的第一个应用程序，以根据一些健康数据绘制一些图形。该应用程序可以像我在本地想象的那样运行，但是当我将其部署在shinyapps.io上时，我仅在第三个选项卡上获得了一个图（运行正常）。但是，前2个选项卡上的绘图无法提供任何信息，即使它需要的数据来自我也已上传的同一文件。
是否有明显的东西我已经错过或做了，以至于无法生成前3个图？
library(tidyverse)
library(shiny)
library(lubridate)
ERAS <- readRDS("ERAS.rda")
ERAS_yearly <- ERAS %>%
arrange(year_m) %>%
mutate(DoSdate = ymd(year_m), yearDoS = year(DoSdate), monthDoS = month(DoSdate)) %>%
group_by(yearDoS) %>%
summarise(year_meanLOS = mean(Postop_LOS),
year_meanAll3 = mean(All_3 == T, na.rm = T),
year_AKI = mean(AKI_pos == T, na.rm = T))
# User Interface
ui <- fluidPage(
titlePanel("NERCI Data"),
sidebarLayout(
sidebarPanel(
print("Choose the following for graphs on Tabs 1 and 2:"),
sliderInput("year", "Select Year:", animate = T,
min = 2016, max = 2019, value = 2016, sep = ""),
checkboxGroupInput("approach", "Surgical Approach", c("Laparoscopic", "Lap-assisted", "Converted to open", "Open"),
selected = c("Laparoscopic", "Lap-assisted", "Converted to open", "Open")),
print("Choose the following for graph on Tab 3:"),
selectInput("x_axis", "Choose x axis",
c("Surgical Risk" = "Risk",
"Obesity Class" = "Obesity",
"ASA-PS" = "ASA",
"Anaemia" = "Anaemia",
"Acute Kidney Injury" = "AKI_pos",
"DrEaming Goals" = "All_3",
"Surgical Approach" = "Sx_Approach",
"POMS on Day 3" = "posPOMS3",
"POMS on Day 5" = "posPOMS5",
"Re-operation for Leaks" = "Reoperation_Leak",
"Re-operation for Other" = "Reoperation_Other",
"ICU Admission" = "ICU_Admission"),
selected = "Surgical Risk"),
selectInput("y_axis", "Choose y axis",
c("Total Post-op Length of Stay" = "Postop_LOS",
"SHDU Length of Stay" = "HDU_LOS")),
selectInput("extra_filter", "Choose additional info",
c("Surgical Approach" = "Sx_Approach",
"Surgical Risk" = "Risk",
"Obesity Class" = "Obesity"),
selected = "Surgical Approach"),
dateRangeInput("date", "Choose Date Range of Data to display",
start = "2016-02-01", end = Sys.Date(),
min = "2016-02-01", max = Sys.Date())
),
mainPanel(
tabsetPanel(
tabPanel("DrEaMing",
plotOutput(outputId = "LOS_plot"),
plotOutput(outputId = "All3_plot")),
tabPanel("AKI Data",
plotOutput(outputId = "AKI_plot")),
tabPanel("Length of Stay Data",
plotOutput(outputId = "LOS_overall"))
)
)
)
)
# Server
server <- function(input, output){
output$LOS_plot <- renderPlot({
plot1a <- ERAS %>% filter(Sx_Approach %in% input$approach) %>%
arrange(year_m) %>%
mutate(DoSdate = ymd(year_m), yearDoS = year(DoSdate), monthDoS = month(DoSdate)) %>%
filter(yearDoS == input$year) %>%
group_by(year_m) %>%
mutate(mean_LOS = mean(Postop_LOS)) %>%
ggplot(aes(x = monthDoS, y = mean_LOS)) + geom_line(colour = "#A8659C", size = 1.5) +
geom_hline(data = ERAS_yearly[ERAS_yearly$yearDoS == input$year, ], aes(yintercept = year_meanLOS), alpha = 0.4, colour = "#323232") +
scale_x_continuous(limits = c(1, 12), breaks = c(1:12)) +
scale_y_continuous(limits = c(0,30), minor_breaks = 1) +
theme(aspect.ratio = 0.4) + xlab("Month") + ylab("Days") + ggtitle("Mean Length of Stay over Time")
plot1a
})
output$All3_plot <- renderPlot({
plot1b <- ERAS %>% filter(Sx_Approach %in% input$approach) %>%
arrange(year_m) %>%
mutate(DoSdate = ymd(year_m), yearDoS = year(DoSdate), monthDoS = month(DoSdate)) %>%
filter(yearDoS == input$year) %>% group_by(year_m) %>%
mutate(mean_All3 = mean(All_3 == T, na.rm = T)) %>%
ggplot(aes(x = monthDoS, y = mean_All3)) + geom_line(colour = "#116133", size = 1.5) +
geom_hline(data = ERAS_yearly[ERAS_yearly$yearDoS == input$year, ], aes(yintercept = year_meanAll3), alpha = 0.4, colour = "#323232") +
scale_x_continuous(limits = c(1, 12), breaks = c(1:12)) +
scale_y_continuous(labels = scales::percent, limits = c(0, 1)) +
theme(aspect.ratio = 0.4) + xlab("Month") + ylab("Percentage") + ggtitle("Patients Achieving All Three ERAS Goals")
plot1b
})
output$AKI_plot <- renderPlot({
plot2 <- ERAS %>% filter(Sx_Approach %in% input$approach) %>%
arrange(year_m) %>%
mutate(DoSdate = ymd(year_m), yearDoS = year(DoSdate), monthDoS = month(DoSdate)) %>%
filter(yearDoS == input$year) %>% group_by(year_m) %>%
mutate(mean_AKI = mean(AKI_pos == T, na.rm = T)) %>%
ggplot(aes(x = monthDoS, y = mean_AKI)) + geom_line(colour = "#FDDB2E", size = 1.5) +
geom_hline(data = ERAS_yearly[ERAS_yearly$yearDoS == input$year, ], aes(yintercept = year_AKI), alpha = 0.4, colour = "#323232") +
scale_x_continuous(limits = c(1, 12), breaks = c(1:12)) +
scale_y_continuous(labels = scales::percent, limits = c(0, 1)) +
theme(aspect.ratio = 0.4) + xlab("Month") + ylab("Percentage") + ggtitle("Percentage of Patients with Post-op AKI")
plot2
})
output$LOS_overall <- renderPlot({
x <- input$x_axis
y <- input$y_axis
extra <- input$extra_filter
ERAS <- filter(ERAS, DoS >= input$date[1] & DoS <= input$date[2])
plot03 <- ggplot(data = ERAS, aes_string(x = x, y = y)) +
geom_jitter(aes_string(colour = extra), alpha = 0.5, size = 5) +
geom_boxplot(alpha = 0.5) +
ggtitle("Length of Stay Post-op") + xlab(x) + ylab("Length of Stay") +
theme(aspect.ratio = 0.6)
plot03
})
}
shinyApp(ui = ui, server = server)