首先，免责声明：我参加了Coursera＆＃34;开发数据产品＆＃34;课程。我上个月在课程中，但工作义务占用了我很多时间，我无法在截止日期前完成课程。我继续从事该课程项目，并重新注册了刚刚开始的1月份课程。
我通过RStudio.com观看了关于Shiny特定网站上的课程和教程系列的视频。我有一切工作，除了ggplot的绘图输出。问题是没有输出。也没有错误消息。我无法弄明白，所以我希望有人能够看到我的代码，并指出我正确的方向。
我的R代码如下。
谢谢！ （提前。）
富
ui.R：
## Coursera Data Science Specialization
# Class: Delivering Data Products
#
# Author: Richard Ian Carpenter
# Date Created: 14 Dec 2015
# Data Updated: 06 Jan 2016
#
## NOTES:
#
## I am repeating this course, unrolled from Dec 2015 course due to work obligations.
#
## Beyond the notes and videos for the class and the Shiny website, I used the
# following:
#
## This Stack Overflow question from 2013 helped with correcting my R code:
# http://stackoverflow.com/questions/18762962/passing-variable-names-to-model-in-shiny-app
#
## This shiny example to get the regression output to be in the same format
# that R uses, instead of a table: https://rich.shinyapps.io/regression/
#
library(shiny)
library(ggplot2)
data("mtcars")
mtcars <- mtcars
ui <- fluidPage(
sidebarPanel(
selectInput("dependent", "Dependent Variable:", c(names(mtcars))),
uiOutput("independent"),
checkboxInput("factor", "Create factor variables (am, cyl, etc.)?")
),
mainPanel(
tabsetPanel(
tabPanel("Regression Plot",
plotOutput("regPlot")),
tabPanel("Regression Summary",
verbatimTextOutput("regSummary")))
)
)
server.R：
## Coursera Data Science Specialization
# Class: Delivering Data Products
#
# Author: Richard Ian Carpenter
# Date Created: 14 Dec 2015
# Data Updated: 06 Jan 2016
#
## NOTES:
#
## I am repeating this course, unrolled from Dec 2015 course due to work obligations.
#
## Beyond the notes and videos for the class and the Shiny website, I used the
# following:
#
## This Stack Overflow question from 2013 helped with correcting my R code:
# http://stackoverflow.com/questions/18762962/passing-variable-names-to-model-in-shiny-app
#
## This shiny example to get the regression output to be in the same format
# that R uses, instead of a table: https://rich.shinyapps.io/regression/
#
library(shiny)
library(ggplot2)
data("mtcars")
mtcars <- mtcars
server <- (function(input, output) {
output$independent <- renderUI({
checkboxGroupInput(
"independent", "Independent Variables:",
names(mtcars)[!names(mtcars) %in% input$dependent],
if(input$factor) {
mtcars$cyl <- as.factor(mtcars$cyl)
mtcars$vs <- as.factor(mtcars$vs)
mtcars$am <- as.factor(mtcars$am)
mtcars$gear <- as.factor(mtcars$gear)
mtcars$carb <- as.factor(mtcars$carb)
}
)
})
regression <- reactive({
lm(paste(input$dependent," ~ ",
paste(input$independent,
collapse = " + ")),
data = mtcars)
})
output$regPlot <- reactive({
renderPlot({p <- ggplot(regression(),
aes(x = paste(input$independent, collapse = " + "),
y = input$dependent,
environment = environment())
)
p <- p + geom_point() #+ geom_smooth()
print(p)
}, height = 700)
})
output$regSummary <- renderPrint({
if(!is.null(input$independent)){
summary(regression())
} else {
print("Please select the model's dependent and independent variables.")
}
})
})