在具有用户选择列的闪亮应用程序中使用自动绘图
Using autoplotly in shiny app with user selected columns
我正在制作一个闪亮的应用程序,允许用户上传 CSV,然后 select 自变量和因变量。现在我可以上传文件、select 变量和 运行 回归分析。但是,我停留在将 lm
对象传递给 autoplot
然后通过新选项卡中的 autoplotly
使其交互的步骤。如何通过在闪亮的应用程序中使用用户 selected 变量来创建交互式回归图?
UI
ui = navbarPage(tabPanel("Regression Analysis",
dataTableOutput('mytable'),
sidebarLayout(
sidebarPanel(width=3, fileInput("file1", "Please choose a CSV file",
multiple = T,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
tags$hr(),
checkboxInput("header", "Header", TRUE),
radioButtons("sep", "Separator",
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ","),
radioButtons("quote", "Quote",
choices = c(None = "",
"Double Quote" = '"',
"Single Quote" = "'"),
selected = '"'),
tags$hr(),
radioButtons("disp", "Display",
choices = c(Head = "head",
All = "all"),
selected = "head")
),
mainPanel(
tableOutput("contents"),
actionButton("choice", "Define Regression Variables"),
selectInput("independent", "Independent Variables:", choices = NULL, multiple = T),
uiOutput("dependent1"),
#tableOutput("Table_selected.col"),
verbatimTextOutput("regTab")
)
),
tabPanel("Plots",
icon = icon("chart-area"),
plotlyOutput(outputId = "RegPlots"))
)
服务器
server = function(input, output, session) {
mydf <- reactive({
# input$file1 will be NULL initially. After the user selects
# and uploads a file, head of that data file by default,
# or all rows if selected, will be shown.
req(input$file1)
df = read.csv(input$file1$datapath,
header = input$header,
sep = input$sep,
quote = input$quote)
if(input$disp == "head") {
return(head(df))
}
else {
return(df)
}
})
output$contents = renderTable({
req(mydf())
mydf()
})
# Code for allowing the user to select the variables/columns of interest
info <- eventReactive(input$choice, {
req(mydf())
f <- mydf()
f
})
observeEvent(input$choice, { ## to update only when you click on the actionButton
req(info())
updateSelectInput(session,"independent", "Please Select independent Variable(s):", choices = names(info()) )
})
# output$Table_selected.col <- renderTable({
# input$choice
# req(info(),input$columns)
# f = info()
# f = subset(f, select = input$columns) #subsetting takes place here
# head(f)
# })
output$dependent1 = renderUI({
req(mydf(),input$independent)
radioButtons("dependent1", "Select a dependent Variable:",choices=names(mydf())[!names(mydf()) %in% input$independent])
})
### need to build your formuila correctly; It will work with multiple independent variables
### model <- reactive({lm(reformulate(input$IndVar, input$DepVar), data = RegData)})
runRegression <- reactive({
req(mydf(),input$independent,input$dependent1)
a = lm(reformulate(input$independent, input$dependent1), data=mydf())
a
# multinom(reformulate(input$independent, input$dependent1), data=mydf()) ### mulitnomial from nnet package
})
output$regTab = renderPrint({
req(runRegression())
if(!is.null(input$independent)){
summary(runRegression())
} else {
print(data.frame(Warning="Please select Model Parameters."))
}
})
}
output$RegPlots = renderPlotly({
req(runRegression())
# Plot the residuals
lm.plot.rsd = autoplot(a, label.size = 3, which = 1) +
theme_bw()
autoplotly(lm.plot.rsd +
ggplot2::ggtitle("Residuals vs Fitted"))
})
shinyApp(ui, server)
错误
Error in : Objects of type function not supported by autoplot.
试试这个
output$RegPlots = renderPlot({
req(runRegression())
# Plot the residuals
a = runRegression()
ggplot(a, aes(x = .fitted, y = .resid)) +
geom_point() +
geom_smooth(method = loess, formula = y ~ x) +
labs(title="Residuals vs Fitted")
})
其他剧情可以试试
我正在制作一个闪亮的应用程序,允许用户上传 CSV,然后 select 自变量和因变量。现在我可以上传文件、select 变量和 运行 回归分析。但是,我停留在将 lm
对象传递给 autoplot
然后通过新选项卡中的 autoplotly
使其交互的步骤。如何通过在闪亮的应用程序中使用用户 selected 变量来创建交互式回归图?
UI
ui = navbarPage(tabPanel("Regression Analysis",
dataTableOutput('mytable'),
sidebarLayout(
sidebarPanel(width=3, fileInput("file1", "Please choose a CSV file",
multiple = T,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
tags$hr(),
checkboxInput("header", "Header", TRUE),
radioButtons("sep", "Separator",
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ","),
radioButtons("quote", "Quote",
choices = c(None = "",
"Double Quote" = '"',
"Single Quote" = "'"),
selected = '"'),
tags$hr(),
radioButtons("disp", "Display",
choices = c(Head = "head",
All = "all"),
selected = "head")
),
mainPanel(
tableOutput("contents"),
actionButton("choice", "Define Regression Variables"),
selectInput("independent", "Independent Variables:", choices = NULL, multiple = T),
uiOutput("dependent1"),
#tableOutput("Table_selected.col"),
verbatimTextOutput("regTab")
)
),
tabPanel("Plots",
icon = icon("chart-area"),
plotlyOutput(outputId = "RegPlots"))
)
服务器
server = function(input, output, session) {
mydf <- reactive({
# input$file1 will be NULL initially. After the user selects
# and uploads a file, head of that data file by default,
# or all rows if selected, will be shown.
req(input$file1)
df = read.csv(input$file1$datapath,
header = input$header,
sep = input$sep,
quote = input$quote)
if(input$disp == "head") {
return(head(df))
}
else {
return(df)
}
})
output$contents = renderTable({
req(mydf())
mydf()
})
# Code for allowing the user to select the variables/columns of interest
info <- eventReactive(input$choice, {
req(mydf())
f <- mydf()
f
})
observeEvent(input$choice, { ## to update only when you click on the actionButton
req(info())
updateSelectInput(session,"independent", "Please Select independent Variable(s):", choices = names(info()) )
})
# output$Table_selected.col <- renderTable({
# input$choice
# req(info(),input$columns)
# f = info()
# f = subset(f, select = input$columns) #subsetting takes place here
# head(f)
# })
output$dependent1 = renderUI({
req(mydf(),input$independent)
radioButtons("dependent1", "Select a dependent Variable:",choices=names(mydf())[!names(mydf()) %in% input$independent])
})
### need to build your formuila correctly; It will work with multiple independent variables
### model <- reactive({lm(reformulate(input$IndVar, input$DepVar), data = RegData)})
runRegression <- reactive({
req(mydf(),input$independent,input$dependent1)
a = lm(reformulate(input$independent, input$dependent1), data=mydf())
a
# multinom(reformulate(input$independent, input$dependent1), data=mydf()) ### mulitnomial from nnet package
})
output$regTab = renderPrint({
req(runRegression())
if(!is.null(input$independent)){
summary(runRegression())
} else {
print(data.frame(Warning="Please select Model Parameters."))
}
})
}
output$RegPlots = renderPlotly({
req(runRegression())
# Plot the residuals
lm.plot.rsd = autoplot(a, label.size = 3, which = 1) +
theme_bw()
autoplotly(lm.plot.rsd +
ggplot2::ggtitle("Residuals vs Fitted"))
})
shinyApp(ui, server)
错误
Error in : Objects of type function not supported by autoplot.
试试这个
output$RegPlots = renderPlot({
req(runRegression())
# Plot the residuals
a = runRegression()
ggplot(a, aes(x = .fitted, y = .resid)) +
geom_point() +
geom_smooth(method = loess, formula = y ~ x) +
labs(title="Residuals vs Fitted")
})
其他剧情可以试试