如何从 R Shiny selectInput() 中的列表中提取元素名称而不是值?
How to extract element name, not value, from a list in R Shiny selectInput()?
我想从 R Shiny 的 selectInput()
中用于 choices
参数的列表中提取元素名称,而不是特定值。
selectInput
函数如下所示:
# ...
selectInput("xvar", "What is the predictor variable?",
choices = list("MPG" = "mpg",
"Cylinders" = "cyl",
"Engine Displacement" = "disp",
"Horse Power" = "hp",
"Gears" = "gear"),
# ...
在我的 server.R
代码中,我想使用“Cylinders”而不是“cyl”作为轴标签。例如(使用 ggplot2
):
# ...
labs(x = input$xvar, y = input$yvar) +
# ...
names(input$xvar)
returns NULL
。有什么办法叫input$xvar
和return这个名字吗?
感谢 Paul 的评论、他提供的链接和 this SO 线程,我能够回答我的问题。
下面我提供了旧的 ui.R
和 server.R
脚本,它们生成了我不满意的轴标签,以及新的 ui.R
和 server.R
脚本,其中轴标签得到改进。 (新脚本中的更改用 # diff
标记)
旧 ui.R
:
shinyUI(fluidPage(
titlePanel("Fit Regression Line for Chosen Variables and Points"),
sidebarLayout(
sidebarPanel(
h2("Model Specifics"), br(),
selectInput("xvar", "What is the predictor variable?",
choices = list("MPG" = "mpg",
"Cylinders" = "cyl",
"Engine Displacement" = "disp",
"Horse Power" = "hp",
"Gears" = "gear"),
multiple = FALSE),
selectInput("yvar", "What is the outcome variable?",
choices = list("MPG" = "mpg",
"Cylinders" = "cyl",
"Engine Displacement" = "disp",
"Horse Power" = "hp",
"Gears" = "gear"),
multiple = FALSE, selected = "cyl"),
h4("Intercept"), textOutput("int"),
h4("Slope"), textOutput("slope")
),
mainPanel(
br(), h2("Display"), h4("Drag to select which points to include in model"),
plotOutput("plot", brush = brushOpts(id = "brush1"))
)
)
))
旧 server.R
:
shinyServer(function(input, output) {
model <- reactive({
points <- brushedPoints(mtcars, brush = input$brush1,
xvar = input$xvar,
yvar = input$yvar)
if(nrow(points) <= 1) {
return(NULL)
} else {
lm(as.formula(paste0(input$yvar,
"~", input$xvar)),
data = points)
}
})
output$int <- renderText({
if(is.null(model())) {
"Too few data points selected"
} else {
round(model()[[1]][1], 2)
}
})
output$slope <- renderText({
if(is.null(model())) {
"Too few data points selected"
} else {
round(model()[[1]][2], 2)
}
})
output$plot <- renderPlot({
library(ggplot2)
ggplot(mapping = aes(x = mtcars[, input$xvar],
y = mtcars[, input$yvar])) +
theme_minimal() +
geom_point() +
labs(x = input$xvar, y = input$yvar) +
coord_cartesian(x = c(0, 1.2*max(mtcars[, input$xvar])),
y = c(0, 1.2*max(mtcars[, input$yvar]))) +
if(!is.null(model())) {
geom_abline(intercept = model()[[1]][1], slope = model()[[1]][2],
colour = "red", lwd = 2, alpha = 0.3)
}
})
})
脚本中的更改用 # diff
标记
新 ui.R
:
shinyUI(fluidPage(
titlePanel("Fit Regression Line for Chosen Variables and Points"),
sidebarLayout(
sidebarPanel(
h2("Model Specifics"), br(),
uiOutput("si_xvar"), # diff
uiOutput("si_yvar"), # diff
h4("Intercept"), textOutput("int"),
h4("Slope"), textOutput("slope")
),
mainPanel(
br(), h2("Display"), h4("Drag to select which points to include in model"),
plotOutput("plot", brush = brushOpts(id = "brush1"))
)
)
))
新 server.R
:
shinyServer(function(input, output) {
varlist <- list("MPG" = "mpg", # diff
"Cylinders" = "cyl",
"Engine Displacement" = "disp",
"Horse Power" = "hp",
"Gears" = "gear")
output$si_xvar <- renderUI( # diff
selectInput("xvar", "What is the predictor variable?",
choices = varlist,
multiple = FALSE)
)
output$si_yvar <- renderUI( # diff
selectInput("yvar", "What is the outcome variable?",
choices = varlist,
multiple = FALSE, selected = "cyl")
)
model <- reactive({
points <- brushedPoints(mtcars, brush = input$brush1,
xvar = input$xvar,
yvar = input$yvar)
if(nrow(points) <= 1) {
return(NULL)
} else {
lm(as.formula(paste0(input$yvar,
"~", input$xvar)),
data = points)
}
})
output$int <- renderText({
if(is.null(model())) {
"Too few data points selected"
} else {
round(model()[[1]][1], 2)
}
})
output$slope <- renderText({
if(is.null(model())) {
"Too few data points selected"
} else {
round(model()[[1]][2], 2)
}
})
output$plot <- renderPlot({
library(ggplot2)
ggplot(mapping = aes(x = mtcars[, input$xvar],
y = mtcars[, input$yvar])) +
theme_minimal() +
geom_point() +
labs(x = names(which(input$xvar == varlist)), # diff
y = names(which(input$yvar == varlist))) + # diff
coord_cartesian(x = c(0, 1.2*max(mtcars[, input$xvar])),
y = c(0, 1.2*max(mtcars[, input$yvar]))) +
if(!is.null(model())) {
geom_abline(intercept = model()[[1]][1], slope = model()[[1]][2],
colour = "red", lwd = 2, alpha = 0.3)
}
})
})
我想从 R Shiny 的 selectInput()
中用于 choices
参数的列表中提取元素名称,而不是特定值。
selectInput
函数如下所示:
# ...
selectInput("xvar", "What is the predictor variable?",
choices = list("MPG" = "mpg",
"Cylinders" = "cyl",
"Engine Displacement" = "disp",
"Horse Power" = "hp",
"Gears" = "gear"),
# ...
在我的 server.R
代码中,我想使用“Cylinders”而不是“cyl”作为轴标签。例如(使用 ggplot2
):
# ...
labs(x = input$xvar, y = input$yvar) +
# ...
names(input$xvar)
returns NULL
。有什么办法叫input$xvar
和return这个名字吗?
感谢 Paul 的评论、他提供的链接和 this SO 线程,我能够回答我的问题。
下面我提供了旧的 ui.R
和 server.R
脚本,它们生成了我不满意的轴标签,以及新的 ui.R
和 server.R
脚本,其中轴标签得到改进。 (新脚本中的更改用 # diff
标记)
旧 ui.R
:
shinyUI(fluidPage(
titlePanel("Fit Regression Line for Chosen Variables and Points"),
sidebarLayout(
sidebarPanel(
h2("Model Specifics"), br(),
selectInput("xvar", "What is the predictor variable?",
choices = list("MPG" = "mpg",
"Cylinders" = "cyl",
"Engine Displacement" = "disp",
"Horse Power" = "hp",
"Gears" = "gear"),
multiple = FALSE),
selectInput("yvar", "What is the outcome variable?",
choices = list("MPG" = "mpg",
"Cylinders" = "cyl",
"Engine Displacement" = "disp",
"Horse Power" = "hp",
"Gears" = "gear"),
multiple = FALSE, selected = "cyl"),
h4("Intercept"), textOutput("int"),
h4("Slope"), textOutput("slope")
),
mainPanel(
br(), h2("Display"), h4("Drag to select which points to include in model"),
plotOutput("plot", brush = brushOpts(id = "brush1"))
)
)
))
旧 server.R
:
shinyServer(function(input, output) {
model <- reactive({
points <- brushedPoints(mtcars, brush = input$brush1,
xvar = input$xvar,
yvar = input$yvar)
if(nrow(points) <= 1) {
return(NULL)
} else {
lm(as.formula(paste0(input$yvar,
"~", input$xvar)),
data = points)
}
})
output$int <- renderText({
if(is.null(model())) {
"Too few data points selected"
} else {
round(model()[[1]][1], 2)
}
})
output$slope <- renderText({
if(is.null(model())) {
"Too few data points selected"
} else {
round(model()[[1]][2], 2)
}
})
output$plot <- renderPlot({
library(ggplot2)
ggplot(mapping = aes(x = mtcars[, input$xvar],
y = mtcars[, input$yvar])) +
theme_minimal() +
geom_point() +
labs(x = input$xvar, y = input$yvar) +
coord_cartesian(x = c(0, 1.2*max(mtcars[, input$xvar])),
y = c(0, 1.2*max(mtcars[, input$yvar]))) +
if(!is.null(model())) {
geom_abline(intercept = model()[[1]][1], slope = model()[[1]][2],
colour = "red", lwd = 2, alpha = 0.3)
}
})
})
脚本中的更改用 # diff
新 ui.R
:
shinyUI(fluidPage(
titlePanel("Fit Regression Line for Chosen Variables and Points"),
sidebarLayout(
sidebarPanel(
h2("Model Specifics"), br(),
uiOutput("si_xvar"), # diff
uiOutput("si_yvar"), # diff
h4("Intercept"), textOutput("int"),
h4("Slope"), textOutput("slope")
),
mainPanel(
br(), h2("Display"), h4("Drag to select which points to include in model"),
plotOutput("plot", brush = brushOpts(id = "brush1"))
)
)
))
新 server.R
:
shinyServer(function(input, output) {
varlist <- list("MPG" = "mpg", # diff
"Cylinders" = "cyl",
"Engine Displacement" = "disp",
"Horse Power" = "hp",
"Gears" = "gear")
output$si_xvar <- renderUI( # diff
selectInput("xvar", "What is the predictor variable?",
choices = varlist,
multiple = FALSE)
)
output$si_yvar <- renderUI( # diff
selectInput("yvar", "What is the outcome variable?",
choices = varlist,
multiple = FALSE, selected = "cyl")
)
model <- reactive({
points <- brushedPoints(mtcars, brush = input$brush1,
xvar = input$xvar,
yvar = input$yvar)
if(nrow(points) <= 1) {
return(NULL)
} else {
lm(as.formula(paste0(input$yvar,
"~", input$xvar)),
data = points)
}
})
output$int <- renderText({
if(is.null(model())) {
"Too few data points selected"
} else {
round(model()[[1]][1], 2)
}
})
output$slope <- renderText({
if(is.null(model())) {
"Too few data points selected"
} else {
round(model()[[1]][2], 2)
}
})
output$plot <- renderPlot({
library(ggplot2)
ggplot(mapping = aes(x = mtcars[, input$xvar],
y = mtcars[, input$yvar])) +
theme_minimal() +
geom_point() +
labs(x = names(which(input$xvar == varlist)), # diff
y = names(which(input$yvar == varlist))) + # diff
coord_cartesian(x = c(0, 1.2*max(mtcars[, input$xvar])),
y = c(0, 1.2*max(mtcars[, input$yvar]))) +
if(!is.null(model())) {
geom_abline(intercept = model()[[1]][1], slope = model()[[1]][2],
colour = "red", lwd = 2, alpha = 0.3)
}
})
})