我正在 Shiny 中构建我的第一个应用程序，我一直想更好地了解反应性。我已经浏览了http://shiny.rstudio.com/tutorial/上的教程。我正在研究一个与网球相关的数据集，并希望使用“radarchart”包创建一个雷达图。我能够使用反应式表达式成功呈现单选按钮并选择输入框。
然而，点击“开始！” 按钮，控制台显示以下错误：“filter_impl 中的错误：长度不正确 (0)，预期：27”。不过，应用程序本身没有显示错误，点击“开始！”时没有渲染 按钮。
调试时，我看到当我尝试使用用户选择的输入值（server.R 中的第 60-63 行）过滤数据时发生此错误。我主要关心的是根据用户的选择过滤数据，我无法以任何方式做到这一点。我也尝试过使用 eventReactive()、observe() 以及 reactiveValues() 函数，但没有成功。我已将 renderChartJSRadar 函数包装在 eventReactive 函数中，但我不太确定这是否是正确的方法。
我对这种情况下的反应性应该如何工作以及我缺少什么使其工作感到困惑。代码如下所示。我真的很感激任何帮助。
用户界面
library(xlsx)
library(shiny)
library(dplyr)
source("chart.R")
library(radarchart)
shinyUI(fluidPage(
titlePanel("Match Radar Chart"),
sidebarLayout(
sidebarPanel(
selectInput("var",
label = "Choose a tournament",
choices = tour,
selected = "Auckland"),
uiOutput("radioButtons"),
uiOutput("selectControls"),
actionButton("update", "Go!")
),
mainPanel(
chartJSRadarOutput("radarChart", width = "450", height = "300")
)
)
))
服务器.R
library(xlsx)
library(dplyr)
library(radarchart)
library(data.table)
source("chart.R")
library(shiny)
library(grDevices)
shinyServer(function(input, output, session) {
output$radioButtons <- renderUI({
dataInput <- reactive({input$var})
z <- dataInput()
buttons <- numrounds(z)
radioButtons("button", "Select a round: ", choices = buttons, inline = FALSE)
})
output$selectControls <- renderUI({
dataInput <- reactive({input$var})
z <- dataInput()
dataInput1 <- reactive({input$button})
y <- dataInput1()
winner <- mydata %>%
filter(tourney_name == z) %>%
filter(round == y) %>%
select(winner_name) %>%
sapply(as.character) %>%
as.vector()
loser <- mydata %>%
filter(tourney_name == z) %>%
filter(round == y) %>%
select(loser_name) %>%
sapply(as.character) %>%
as.vector()
players <- c(winner, loser)
selectInput("select", "Select a match: ", choices = players, selected = 1, multiple = FALSE)
})
output$radarChart <- eventReactive(input$update, {
renderChartJSRadar({
dataInput1 <- reactive({input$var})
z <- dataInput1()
dataInput2 <- reactive({input$button})
y <- dataInput2()
dataInput3 <- reactive({input$select})
x <- dataInput3()
match <- mydata %>%
filter(tourney_name == z) %>%
filter(round == y) %>%
filter(winner_name == x)
scoresw <- vector()
scoresl <- vector()
for(j in 25:33) {
scoresw <- c(scoresw, match()[j])
}
for(j in 34:42) {
scoresl <- c(scoresl, match()[j])
}
scores <- list(winner = scoresw, loser = scoresl)
labs <- c("Aces", "Double Faults", "Service points", "1st Service In", "1st Service won", "2nd Service won", "Service games", "Break points saved", "Break points faced")
c <- grDevices::col2rgb(c("green", "red"))
chartJSRadar(scores = scores, labs = labs, labelSize = 15, colMatrix = c)
})
})
})
图表.R
mydata <- read.csv("Match Radar/Data/atp_matches_2014_edited.csv", header = TRUE)
tour <- unique(data$tourney_name)
numrounds <- function(z) {
for(i in 1:64) {
rounds <- mydata %>%
filter(tourney_name == z) %>%
summarise(number = n_distinct(round))
if(rounds == 3){
buttons <- c("RR", "SF", "F")
}
else if(rounds == 5){
buttons <- c("R32", "R16", "QF", "SF", "F")
}
else if(rounds == 6){
buttons <- c("R64", "R32", "R16", "QF", "SF", "F")
}
else {
buttons <- c("R128", "R64", "R32", "R16", "QF", "SF", "F")
}
}
buttons
}