RShiny中的被动数据问题

我正在为一个个人项目制作一个闪亮的仪表盘，上面有一些足球数据。每当我更改要绘制的统计数据和/或过滤器时，我都会得到与第一个数据集中相同的玩家。例如，当我启动该应用程序时，该应用程序会创建一个学校历史上排名前十的冲刺者的图表，其中冲刺尝试次数的过滤器大于等于0。但是，当我将统计选择更改为“快速平均”时，显示的是这十名玩家，这是不正确的

library(readxl)
library(tidyverse)
library(purrr)
library(shiny)

interface <- fluidPage(
    titlePanel(" "), 
    sidebarLayout(
        sidebarPanel(
            h1("Stats!"), 
            selectInput("stat_selection", 
                        label = "Select a season statistics", 
                        choices = c("Rushing Yards",
                                    "Rushing Touchdowns",
                                    "Rushing Average",
                                    "Reciving Yards",
                                    "Receptions",
                                    "Receiving Touchdowns",
                                    "Receiving Average"),
                        selected = "Rushing Yards"), 
            selectInput("filter_input", 
                        label = "Select a statistic to filter by", 
                        choices = c("Rushing Yards",
                                    "Rushing Touchdowns",
                                    "Rushing Average",
                                    "Rushing Attempts",
                                    "Reciving Yards",
                                    "Receptions",
                                    "Receiving Touchdowns",
                                    "Receiving Average"),
                        selected = "Rushing Attempts"), 
            numericInput("filter_number", 
                         label = "Type a number for the filter (>=)", 
                         value = 0, min = 0), 
            actionButton("button", "Graph")), 
        mainPanel(
            plotOutput("plot_button"),
            tableOutput("table_button")
        )
    )
)

server_osu <- function(input, output) {
    dataInput <- reactive({
        switch(input$stat_selection, 
               "Rushing Yards" = rush_yds, 
               "Rushing Touchdowns" = rush_tds, 
               "Rushing Average" = rush_avg,
               "Reciving Yards" = rec_yds,
               "Receptions" = rec_rec,
               "Receiving Touchdowns" = rec_td,
               "Receiving Average" = rec_avg)
    })
    filterInput <- reactive({
        switch(input$filter_input, 
               "Rushing Yards" = rush_yds, 
               "Rushing Touchdowns" = rush_tds, 
               "Rushing Average" = rush_avg,
               "Rushing Attempts" = rush_att,
               "Reciving Yards" = rec_yds,
               "Receptions" = rec_rec,
               "Receiving Touchdowns" = rec_td,
               "Receiving Average" = rec_avg)
    })
    filter_number <- reactive(as.double(input$filter_number))
    table_button_react <- eventReactive(input$button, {
        dataset <- dataInput()
        val <- filter_number()
        colnames(dataset)[1] = "Player and Season"
        dataset_filter <- filterInput()
        colnames(dataset_filter)[1] = "Player and Season"
        dataset <- left_join(dataset, dataset_filter)
        colnames(dataset)[1] = "Player and Season"
        og <- colnames(dataset)[3]
        colnames(dataset)[3] = "filter"
        original <- colnames(dataset)[2]
        colnames(dataset)[2] = 'selected'
        dataset <- dataset %>% 
            filter(filter >= val)
        dataset <- dataset %>% 
            top_n(10) %>% 
            arrange(-selected)
        colnames(dataset)[2] = original
        colnames(dataset)[3] = og
        dataset
    })
    plot_button_react <- eventReactive(input$button, {
        dataset <- dataInput()
        val <- filter_number()
        colnames(dataset)[1] = "Player and Season"
        dataset_filter <- filterInput()
        colnames(dataset_filter)[1] = "Player and Season"
        dataset <- left_join(dataset, dataset_filter)
        colnames(dataset)[1] = "Player and Season"
        colnames(dataset)[2] = "selected"
        colnames(dataset)[3] = "filter"
        dataset <- dataset %>% 
            filter(filter >= val)
        top_ten <- dataset %>% top_n(10)
        min = min(top_ten$selected)
        max = max(top_ten$selected)
        ggplot(top_ten, aes(x = reorder(`Player and Season`, -selected), y = selected)) +
            geom_bar(stat = 'identity') + theme_minimal() + xlab('SEASON') +
            ylab(input$stat_selection) + theme(text=element_text(size=16)) +
            scale_fill_manual(values = c('#BBBBBB', '#BB0000')) +
            theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
            theme(legend.position = 'none') +
            coord_cartesian(ylim=c(min - 0.05*min, max + 0.05*max)) +
            theme(axis.title.y = element_text(margin = margin(t = 0, r = 10, b = 0, l = 10))) +
            theme(axis.title.x = element_text(margin = margin(t = 10, r = 0, b = 10, l = 0))) +
            theme(axis.text.y = element_text(size=14),
                  axis.title=element_text(size=16,face='bold')) + 
            labs(caption = '')
    })
    output$plot_button <- renderPlot({
        plot_button_react()
    })
    output$table_button <- renderTable({
        table_button_react()
    })
}

库（readxl）
图书馆（tidyverse）
图书馆（purrr）
图书馆（闪亮）
界面正如我上面提到的，reprex（包括输入数据）将帮助我们帮助您。也就是说，我认为问题在于您的
XXX\u按钮的反应
s仅依赖于
input$button
。它们不依赖于
输入$stat\u选择
，
输入$filter\u编号
或
输入$filter\u输入
。这就是为什么他们没有按照你的要求进行更新

修复很容易。只需将它们（在调用
req（）
的过程中，如果您愿意）添加到每个
XXXX\u按钮的顶部，例如：

plot_button_react <- eventReactive(input$button, {
  input$stat_selection
  input$filter_number
  input$filter_input

  <your code here>
})

plot_button_react正如我前面提到的，reprex（包括输入数据）将帮助我们帮助您。也就是说，我认为问题在于您的
XXX\u按钮的反应
s仅依赖于
input$button
。它们不依赖于
输入$stat\u选择
，
输入$filter\u编号
或
输入$filter\u输入
。这就是为什么他们没有按照你的要求进行更新

修复很容易。只需将它们（在调用
req（）
的过程中，如果您愿意）添加到每个
XXXX\u按钮的顶部，例如：

plot_button_react <- eventReactive(input$button, {
  input$stat_selection
  input$filter_number
  input$filter_input

  <your code here>
})

plot\u按钮\u？哦，你是说“足球”！；）说真的，如果你在应用程序中加入一些输入数据并删除一些不相关的功能，那么帮助你会更容易。那会使你更容易得到帮助。有关如何制作简单的自包含示例或reprex.Football的建议，请参阅？哦，你是说“足球”！；）说真的，如果你在应用程序中加入一些输入数据并删除一些不相关的功能，那么帮助你会更容易。那会使你更容易得到帮助。有关如何制作简单的自包含示例或reprex的建议，请参阅。