我正在用鼠标悬停在ggplot 2极地光泽的标签上。
我的代码的简单版本(没有鼠标悬停在标签上):
library(dplyr)
library(shiny)
library(ggplot2)
# Define UI for application that plots features of iris
ui <- fluidPage(
br(),
# Sidebar layout
sidebarLayout(
# Inputs
sidebarPanel(
),
# Outputs
mainPanel(
plotOutput(outputId = "radarplot"),
br()
)
)
)
# Define server function required to create the radarplot
server <- function(input, output) {
# Create radarplot with iris dataset
output$radarplot <- renderPlot ({
iris %>%
ggplot(.) + geom_histogram(aes(y = Petal.Width, x = Species, fill = Species),
binwidth= 1,
stat= 'identity',
alpha = 1 ) +
geom_histogram(aes(y = Sepal.Width, x = Species, fill = Species),
binwidth= 1,
stat= 'identity',
alpha = 0.3) +
coord_polar()
})
}
# Create a Shiny app object
shinyApp(ui = ui, server = server)
我使用plotly制作了一个版本,试图在标签上添加鼠标。但是然后我没有得到雷达图。
library(dplyr)
library(shiny)
library(ggplot2)
library(plotly)
# Define UI for application that plots features of iris
ui <- fluidPage(
br(),
# Sidebar layout
sidebarLayout(
# Inputs
sidebarPanel(
),
# Outputs
mainPanel(
plotlyOutput(outputId = "radarplot"),
br()
)
)
)
# Define server function required to create the radarplot
server <- function(input, output) {
# Create radarplot with iris dataset
output$radarplot <- renderPlotly ({
iris %>%
ggplot(.) + geom_histogram(aes(y = Petal.Width, x = Species, fill = Species),
binwidth= 1,
stat= 'identity',
alpha = 1 ) +
geom_histogram(aes(y = Sepal.Width, x = Species, fill = Species),
binwidth= 1,
stat= 'identity',
alpha = 0.3) +
coord_polar()
})
}
# Create a Shiny app object
shinyApp(ui = ui, server = server)
理想情况下,当鼠标悬停在特定的“翅膀”上时,我希望鼠标悬停标签提供有关Petal.Width,Sepal.Width和Species的输出。
任何建议如何将这些鼠标悬停在标签上?
答案 0 :(得分:1)
以下是使用ggiraph
软件包的示例。
首先,需要创建工具提示。
library(tidyverse)
iris_group_means <-
iris %>%
group_by(Species) %>%
summarise_all(mean) %>%
mutate(tooltip = sprintf("Sepal Length: %1.2f\nSepal Width: %1.2f\nPetal Length: %1.2f\nPetal Width: %1.2f",
Sepal.Length, Sepal.Width, Petal.Length, Petal.Width)) %>%
select(Species, tooltip)
然后,仅出于美观目的提供此工具提示,而不是geom_histogram
,请使用ggiraph::geom_histogram_interactive
函数。
my_gg <-
iris %>%
ggplot() +
geom_histogram(aes(y = Petal.Width, x = Species, fill = Species),
binwidth= 1,
stat= 'identity',
alpha = 1 ) +
ggiraph::geom_histogram_interactive(aes(y = Sepal.Width, x = Species, fill = Species, tooltip = tooltip),
binwidth= 1,
stat= 'identity',
alpha = 0.3) +
coord_polar()
ggiraph::ggiraph(code = print(my_gg))
然后可以在Shiny中使用。涉及其他几个步骤,并且有一个单独的ggiraph::renderggiraph
函数要使用。详细信息在ggiraph site
这是最终的Shiny代码。我没有太多使用Shiny,因此可以对其进行改进,但对我有用。
# Define UI for application that plots features of iris
ui <- fluidPage(
br(),
# Sidebar layout
sidebarLayout(
# Inputs
sidebarPanel(
),
# Outputs
mainPanel(
ggiraph::ggiraphOutput(outputId = "radarplot"),
br()
)
)
)
# Define server function required to create the radarplot
server <- function(input, output) {
# Create radarplot with iris dataset
output$radarplot <- ggiraph::renderggiraph ({
iris_group_means <-
iris %>%
group_by(Species) %>%
summarise_all(mean) %>%
mutate(tooltip = sprintf("Sepal Length: %1.2f\nSepal Width: %1.2f\nPetal Length: %1.2f\nPetal Width: %1.2f",
Sepal.Length, Sepal.Width, Petal.Length, Petal.Width)) %>%
select(Species, tooltip)
iris <-
left_join(iris, iris_group_means, by="Species")
my_gg <-
iris %>%
ggplot() +
geom_histogram(aes(y = Petal.Width, x = Species, fill = Species),
binwidth= 1,
stat= 'identity',
alpha = 1 ) +
ggiraph::geom_histogram_interactive(aes(y = Sepal.Width, x = Species, fill = Species, tooltip = tooltip),
binwidth= 1,
stat= 'identity',
alpha = 0.3) +
coord_polar()
ggiraph::ggiraph(code = print(my_gg))
})
}
# Create a Shiny app object
shinyApp(ui = ui, server = server)