r - 调整闪亮的代码，以便正确呈现图形

Question

我将详细说明这个问题，因为我认为它可以让您更轻松地帮助我确定正在发生的问题。

您将看到两个代码。第一个只是根据某个日期和类别生成图表的功能。根据日期（30/06 和 01/07）和类别（FDE 和 ABC）选项，我可以生成四个不同的图形（我插入了图像供您查看）。如果我只是使用这个功能，它可以正常工作。

但是，我制作了第二个代码来使用与代码 1 相同的功能，但在 Shiny 中。我在 Shiny 中构建了代码，但效果不是很好。该代码仅适用于第一张图，因为我定义了我的dmda和CategoryChosse. 但是，我希望代码能够为两个日期/类别生成。如果碰巧我在闪亮上构建错误，请随意调整它。我愿意接受建议。

第一个代码

library(dplyr)
library(tidyverse)
library(lubridate)

df1 <- structure(
  list(date1= c("2021-06-28","2021-06-28","2021-06-28","2021-06-28"),
       date2 = c("2021-06-30","2021-06-30","2021-07-01","2021-07-01"),
       Category = c("FDE","ABC","FDE","ABC"),
       Week= c("Wednesday","Wednesday","Friday","Friday"),
       DR1 = c(4,1,6,3),
       DR01 = c(4,1,4,3), DR02= c(4,2,6,2),DR03= c(9,5,4,7),
       DR04 = c(5,4,3,2),DR05 = c(5,4,5,4),
       DR06 = c(2,4,3,2),DR07 = c(2,5,4,4),
       DR08 = c(3,4,5,4),DR09 = c(2,3,4,4)),
  class = "data.frame", row.names = c(NA, -4L))


f1 <- function(dmda, CategoryChosse) {

  x<-df1 %>% select(starts_with("DR0"))
  
  x<-cbind(df1, setNames(df1$DR1 - x, paste0(names(x), "_PV")))
  PV<-select(x, date2,Week, Category, DR1, ends_with("PV"))
  
  med<-PV %>%
    group_by(Category,Week) %>%
    summarize(across(ends_with("PV"), median))
  
  SPV<-df1%>%
    inner_join(med, by = c('Category', 'Week')) %>%
    mutate(across(matches("^DR0\\d+$"), ~.x + 
                    get(paste0(cur_column(), '_PV')),
                  .names = '{col}_{col}_PV')) %>%
    select(date1:Category, DR01_DR01_PV:last_col())
  
  SPV<-data.frame(SPV)
  
  mat1 <- df1 %>%
    filter(date2 == dmda, Category == CategoryChosse) %>%
    select(starts_with("DR0")) %>%
    pivot_longer(cols = everything()) %>%
    arrange(desc(row_number())) %>%
    mutate(cs = cumsum(value)) %>%
    filter(cs == 0) %>%
    pull(name)
  
  (dropnames <- paste0(mat1,"_",mat1, "_PV"))
  
  SPV <- SPV %>%
    filter(date2 == dmda, Category == CategoryChosse) %>%
    select(-any_of(dropnames))
  
  datas<-SPV %>%
    filter(date2 == ymd(dmda)) %>%
    group_by(Category) %>%
    summarize(across(starts_with("DR0"), sum)) %>%
    pivot_longer(cols= -Category, names_pattern = "DR0(.+)", values_to = "val") %>%
    mutate(name = readr::parse_number(name))
  colnames(datas)[-1]<-c("Days","Numbers")
  
  datas <- datas %>% 
    group_by(Category) %>% 
    slice((as.Date(dmda) - min(as.Date(df1$date1) [
      df1$Category == first(Category)])):max(Days)+1) %>%
    ungroup
 

  plot(Numbers ~ Days,  xlim= c(0,45), ylim= c(0,30),
       xaxs='i',data = datas,main = paste0(dmda, "-", CategoryChosse))
  
  model <- nls(Numbers ~ b1*Days^2+b2,start = list(b1 = 0,b2 = 0),data = datas, algorithm = "port")
  
  new.data <- data.frame(Days = with(datas, seq(min(Days),max(Days),len = 45)))
  new.data <- rbind(0, new.data)
  lines(new.data$Days,predict(model,newdata = new.data),lwd=2)
  coef<-coef(model)[2]
  points(0, coef, col="red",pch=19,cex = 2,xpd=TRUE)
  text(.99,coef + 1,max(0, round(coef,1)), cex=1.1,pos=4,offset =1,col="black")
  
}

f1("2021-06-30", "FDE")
f1("2021-06-30", "ABC")
f1("2021-07-01", "FDE")
f1("2021-07-01", "ABC")

第二个代码

library(shiny)
library(shinythemes)
library(dplyr)
library(tidyverse)
library(lubridate)
library(stringr)

function.test<-function(dmda,CategoryChosse){
  
  df1 <- structure(
    list(date1= c("2021-06-28","2021-06-28","2021-06-28","2021-06-28"),
         date2 = c("2021-06-30","2021-06-30","2021-07-01","2021-07-01"),
         Category = c("FDE","ABC","FDE","ABC"),
         Week= c("Wednesday","Wednesday","Friday","Friday"),
         DR1 = c(4,1,6,3),
         DR01 = c(4,1,4,3), DR02= c(4,2,6,2),DR03= c(9,5,4,7),
         DR04 = c(5,4,3,2),DR05 = c(5,4,5,4),
         DR06 = c(2,4,3,2),DR07 = c(2,5,4,4),
         DR08 = c(3,4,5,4),DR09 = c(2,3,4,4)),
    class = "data.frame", row.names = c(NA, -4L))
  

  dmda<-"2021-06-30"
  CategoryChosse<-"FDE"
  
  f1 <- function(dmda, CategoryChosse) {
    
      x<-df1 %>% select(starts_with("DR0"))
    
    x<-cbind(df1, setNames(df1$DR1 - x, paste0(names(x), "_PV")))
    PV<-select(x, date2,Week, Category, DR1, ends_with("PV"))
    
    med<-PV %>%
      group_by(Category,Week) %>%
      summarize(across(ends_with("PV"), median))
    
    SPV<-df1%>%
      inner_join(med, by = c('Category', 'Week')) %>%
      mutate(across(matches("^DR0\\d+$"), ~.x + 
                      get(paste0(cur_column(), '_PV')),
                    .names = '{col}_{col}_PV')) %>%
      select(date1:Category, DR01_DR01_PV:last_col())
    
    SPV<-data.frame(SPV)
    
    mat1 <- df1 %>%
      filter(date2 == dmda, Category == CategoryChosse) %>%
      select(starts_with("DR0")) %>%
      pivot_longer(cols = everything()) %>%
      arrange(desc(row_number())) %>%
      mutate(cs = cumsum(value)) %>%
      filter(cs == 0) %>%
      pull(name)
    
    (dropnames <- paste0(mat1,"_",mat1, "_PV"))
    
    SPV <- SPV %>%
      filter(date2 == dmda, Category == CategoryChosse) %>%
      select(-any_of(dropnames))
    
    datas<-SPV %>%
      filter(date2 == ymd(dmda)) %>%
      group_by(Category) %>%
      summarize(across(starts_with("DR0"), sum)) %>%
      pivot_longer(cols= -Category, names_pattern = "DR0(.+)", values_to = "val") %>%
      mutate(name = readr::parse_number(name))
    colnames(datas)[-1]<-c("Days","Numbers")
    
    datas <- datas %>% 
      group_by(Category) %>% 
      slice((as.Date(dmda) - min(as.Date(df1$date1) [
        df1$Category == first(Category)])):max(Days)+1) %>%
      ungroup
    
    plot(Numbers ~ Days,  xlim= c(0,45), ylim= c(0,30),
         xaxs='i',data = datas,main = paste0(dmda, "-", CategoryChosse))
    
    model <- nls(Numbers ~ b1*Days^2+b2,start = list(b1 = 0,b2 = 0),data = datas, algorithm = "port")
    
    new.data <- data.frame(Days = with(datas, seq(min(Days),max(Days),len = 45)))
    new.data <- rbind(0, new.data)
    lines(new.data$Days,predict(model,newdata = new.data),lwd=2)
    coef<-coef(model)[2]
    points(0, coef, col="red",pch=19,cex = 2,xpd=TRUE)
    text(.99,coef + 1,max(0, round(coef,1)), cex=1.1,pos=4,offset =1,col="black")
    
  }
  
 
  Plot1<- f1(dmda, CategoryChosse)
  
  
  return(list(
    "Plot1" = Plot1, 
    date2 = df1$date2,
    data = df1
  ))
}

ui <- fluidPage(
  
  ui <- shiny::navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
                          br(),
                          
                          tabPanel("",
                                   sidebarLayout(
                                     sidebarPanel(
                                       
                                       uiOutput("date"),
                                       uiOutput("mycode"),
                                       br(),
                                       
                                       
                                     ),
                                     
                                     mainPanel(
                                       tabsetPanel(
                                         tabPanel("", plotOutput("graph",width = "100%", height = "600") 
                                         )
                                       ),
                                     ))
                          )))


server <- function(input, output,session) {
  
  data <- reactive(function.test(df1))
  
  output$date <- renderUI({
    all_dates <- seq(as.Date('2021-01-01'), as.Date('2021-01-15'), by = "day")
    disabled <- as.Date(setdiff(all_dates, as.Date(data()$date2)), origin = "1970-01-01")
    dateInput(input = "date2", 
              label = h4("Data"),
              min = min(data()$date2),
              max = max(data()$date2),
              value = min(data()$date2),
              format = "dd-mm-yyyy",
              datesdisabled = disabled)
    
  })
  
  output$mycode <- renderUI({
    req(input$date2)
    df1 <- data()$data
    df2 <- df1[as.Date(df1$date2) %in% input$date2,]
    selectInput("code", label = h4("Code"),choices=unique(df2$Category))
  })
  
  output$graph <- renderPlot({
    req(input$date2,input$code)
    function.test(as.character(input$date2),as.character(input$code))[["Plot1"]]
    
  })

}

shinyApp(ui = ui, server = server)

如果我有这个数据库

  df1 <- structure(
    list(date1= c("2021-06-28","2021-06-28","2021-06-28","2021-06-28","2021-06-28"),
         date2 = c("2021-06-25","2021-06-30","2021-06-30","2021-07-01","2021-07-01"),
         Category = c("FDE", "FDE","ABC","FDE","ABC"),
         Week= c("Tuesday", "Wednesday","Wednesday","Friday","Friday"),
         DR1 = c(2,4,1,6,3),
         DR01 = c(2,4,1,4,3), DR02= c(2,4,2,6,2),DR03= c(2,9,5,4,7),
         DR04 = c(2,5,4,3,2),DR05 = c(2,5,4,5,4),
         DR06 = c(2,2,4,3,2),DR07 = c(2,2,5,4,4),
         DR08 = c(2,3,4,5,4),DR09 = c(2,2,3,4,4)),
    class = "data.frame", row.names = c(NA, -5L))

标签： rshiny

Answer 1

尝试这个

library(shiny)
library(shinythemes)
library(dplyr)
library(tidyverse)
library(lubridate)
library(stringr)

function.test<-function(){
  
  df1 <- structure(
    list(date1= c("2021-06-28","2021-06-28","2021-06-28","2021-06-28"),
         date2 = c("2021-06-30","2021-06-30","2021-07-01","2021-07-01"),
         Category = c("FDE","ABC","FDE","ABC"),
         Week= c("Wednesday","Wednesday","Friday","Friday"),
         DR1 = c(4,1,6,3),
         DR01 = c(4,1,4,3), DR02= c(4,2,6,2),DR03= c(9,5,4,7),
         DR04 = c(5,4,3,2),DR05 = c(5,4,5,4),
         DR06 = c(2,4,3,2),DR07 = c(2,5,4,4),
         DR08 = c(3,4,5,4),DR09 = c(2,3,4,4)),
    class = "data.frame", row.names = c(NA, -4L))
  
  return(df1)
}

  f1 <- function(df1, dmda, CategoryChosse) {
    
    x<-df1 %>% select(starts_with("DR0"))
    
    x<-cbind(df1, setNames(df1$DR1 - x, paste0(names(x), "_PV")))
    PV<-select(x, date2,Week, Category, DR1, ends_with("PV"))
    
    med<-PV %>%
      group_by(Category,Week) %>%
      summarize(across(ends_with("PV"), median))
    
    SPV<-df1%>%
      inner_join(med, by = c('Category', 'Week')) %>%
      mutate(across(matches("^DR0\\d+$"), ~.x + 
                      get(paste0(cur_column(), '_PV')),
                    .names = '{col}_{col}_PV')) %>%
      select(date1:Category, DR01_DR01_PV:last_col())
    
    SPV<-data.frame(SPV)
    
    mat1 <- df1 %>%
      filter(date2 == dmda, Category == CategoryChosse) %>%
      select(starts_with("DR0")) %>%
      pivot_longer(cols = everything()) %>%
      arrange(desc(row_number())) %>%
      mutate(cs = cumsum(value)) %>%
      filter(cs == 0) %>%
      pull(name)
    
    (dropnames <- paste0(mat1,"_",mat1, "_PV"))
    
    SPV <- SPV %>%
      filter(date2 == dmda, Category == CategoryChosse) %>%
      select(-any_of(dropnames))
    
    datas<-SPV %>%
      filter(date2 == ymd(dmda)) %>%
      group_by(Category) %>%
      summarize(across(starts_with("DR0"), sum)) %>%
      pivot_longer(cols= -Category, names_pattern = "DR0(.+)", values_to = "val") %>%
      mutate(name = readr::parse_number(name))
    colnames(datas)[-1]<-c("Days","Numbers")
    
    datas <- datas %>% 
      group_by(Category) %>% 
      slice((as.Date(dmda) - min(as.Date(df1$date1) [
        df1$Category == first(Category)])):max(Days)+1) %>%
      ungroup
    
    plot(Numbers ~ Days,  xlim= c(0,45), ylim= c(0,30),
         xaxs='i',data = datas,main = paste0(dmda, "-", CategoryChosse))
    
    model <- nls(Numbers ~ b1*Days^2+b2,start = list(b1 = 0,b2 = 0),data = datas, algorithm = "port")
    
    new.data <- data.frame(Days = with(datas, seq(min(Days),max(Days),len = 45)))
    new.data <- rbind(0, new.data)
    lines(new.data$Days,predict(model,newdata = new.data),lwd=2)
    coef<-coef(model)[2]
    points(0, coef, col="red",pch=19,cex = 2,xpd=TRUE)
    text(.99,coef + 1,max(0, round(coef,1)), cex=1.1,pos=4,offset =1,col="black")
    
  }
  

ui <- fluidPage(
  
  ui <- shiny::navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
                          br(),
                          
                          tabPanel("",
                                   sidebarLayout(
                                     sidebarPanel(
                                       
                                       uiOutput("date"),
                                       uiOutput("mycode"),
                                       br(),
                                       
                                       
                                     ),
                                     
                                     mainPanel(
                                       tabsetPanel(
                                         tabPanel("", plotOutput("graph",width = "100%", height = "600")
                                         )
                                       ),
                                     ))
                          )))


server <- function(input, output,session) {
  
  data <- reactive(function.test())
  
  output$date <- renderUI({
    req(data())
    all_dates <- seq(as.Date('2021-01-01'), as.Date('2021-01-15'), by = "day")
    disabled <- as.Date(setdiff(all_dates, as.Date(data()$date2)), origin = "1970-01-01")
    dateInput(input = "date2", 
              label = h4("Data"),
              min = min(data()$date2),
              max = max(data()$date2),
              value = min(data()$date2),
              format = "dd-mm-yyyy",
              datesdisabled = disabled)
    
  })
  
  output$mycode <- renderUI({
    req(input$date2)
    df1 <- data()
    df2 <- df1[as.Date(df1$date2) %in% input$date2,]
    selectInput("code", label = h4("Code"),choices=unique(df2$Category))
  })
  
  output$graph <- renderPlot({
    req(input$date2,input$code)
    f1(data(),as.character(input$date2),as.character(input$code))
  })
  
}

shinyApp(ui = ui, server = server)