I have a shiny which has tooltips which show the full text of a long string. I am able to show all this text in a manageable way using str_wrap function in the text argument field for the tooltip.
library(shiny)
library(tidyverse)
library(plotly)
library(stringi)
dat <- mtcars %>%
rownames_to_column(var = "model")
dat[["lorem"]] <- rep(stri_rand_lipsum(n_paragraphs = 1), 32)
ui <- fluidPage(
plotlyOutput("plot1")
)
server <- function(input, output, session) {
output$plot1 <- renderPlotly({
p1 <- dat %>%
ggplot(aes(x = wt, y = mpg,
text = str_wrap(lorem, width = 80))) +
geom_point()
ggplotly(p1, tooltip = "text")
})
}
shinyApp(ui, server)
However, I would like to also include some other labels, for instance model and mpg, with some custom styling (i.e. bolding the column titles), along the lines of:
Cany anyone provide a solution of how to do this - I know how to do it w/o the str_wrap function, but can't figure out how to accomplish this w/ it.
Try this:
library(shiny)
library(tidyverse)
library(plotly)
library(stringi)
dat <- mtcars %>%
rownames_to_column(var = "model")
dat[["lorem"]] <- rep(stri_rand_lipsum(n_paragraphs = 1), 32)
ui <- fluidPage(
plotlyOutput("plot1")
)
server <- function(input, output, session) {
output$plot1 <- renderPlotly({
p1 <- dat %>%
ggplot(aes(x = wt, y = mpg,
text = paste0("<b>Model:</b> ", model, "<br>",
"<b>MPG:</b> ", mpg, "<br>",
str_wrap(paste0("<b>Text:</b> ", lorem), width = 80)
))) +
geom_point()
ggplotly(p1, tooltip = "text")
})
}
shinyApp(ui, server)
R Gugus,
Is there any way to sub-set and view data in data.table by clicking on an interactive plotly or googlevis chart in shiny app?
For example, I would like to see the highlighted row in the picture when I click on the related part on plotly chart generated by the following code:
library(shiny)
library(plotly)
library(DT)
library(dplyr)
shinyApp(
ui = shinyUI(fluidPage(
titlePanel("Movie Ratings!"),
mainPanel(
plotlyOutput("chart", width = "100%"),
dataTableOutput("DToutput")
)
)),
server = function(input, output, session) {
df <- structure(c(106487,495681,1597442,2452577,2065141,2271925,4735484,3555352,8056040,4321887,
2463194,347566,621147,1325727,1123492,800368,761550,1359737,1073726,36,53,141,
41538,64759,124160,69942,74862,323543,247236,112059,16595,37028,153249,427642,
1588178,2738157,2795672,2265696,11951,33424,62469,74720,166607,404044,426967,
38972,361888,1143671,1516716,160037,354804,996944,1716374,1982735,3615225,
4486806,3037122,17,54,55,210,312,358,857,350,7368,8443,6286,1750,7367,14092,
28954,80779,176893,354939,446792,33333,69911,53144,29169,18005,11704,13363,
18028,46547,14574,8954,2483,14693,25467,25215,41254,46237,98263,185986),
.Dim=c(19,5),.Dimnames=list(c("1820-30","1831-40","1841-50","1851-60","1861-70",
"1871-80","1881-90","1891-00","1901-10","1911-20",
"1921-30","1931-40","1941-50","1951-60","1961-70",
"1971-80","1981-90","1991-00","2001-06"),
c("Europe","Asia","Americas","Africa","Oceania")))
df.m <- melt(df)
df.m <- rename(df.m, c(Var1 = "Period", Var2 = "Region"))
output$chart <- renderPlotly({
a <- ggplot(df.m, aes(x = Period, y = value/1e+06,fill = Region)) +
ggtitle("Migration to the United States by Source Region (1820-2006), In Millions")
b <- a + geom_bar(stat = "identity", position = "stack")
p <- ggplotly(b)
p
})
output$DToutput <- renderDataTable({df.m})
})
Ultimate aim is to produce an app where the user can navigate easily by between data and charts anywhere in the app. I have a similar app but written in a different code: http://mqasim.me/sw1000/
Current click events in Plotly return all data in the trace so it will be difficult to isolate elements in the stack. Also, will need to build the plot with plot_ly(). One way to deal with the selected table rows being on a different page is to eliminate the need for pagination.
curveNumber: for mutiple traces, information will be returned in a stacked fashion
See this Plotly tutorial for coupled events and section 2.3 of the Shiny page of DT for selecting rows.
library(shiny)
library(plotly)
library(DT)
library(dplyr)
library(reshape2)
shinyApp(
ui = shinyUI(fluidPage(
titlePanel("Movie Ratings!"),
mainPanel(
plotlyOutput("chart", width = "100%"),
DT::dataTableOutput("DToutput")
)
)),
server = function(input, output, session) {
df <- structure(c(106487,495681,1597442,2452577,2065141,2271925,4735484,3555352,8056040,4321887,
2463194,347566,621147,1325727,1123492,800368,761550,1359737,1073726,36,53,141,
41538,64759,124160,69942,74862,323543,247236,112059,16595,37028,153249,427642,
1588178,2738157,2795672,2265696,11951,33424,62469,74720,166607,404044,426967,
38972,361888,1143671,1516716,160037,354804,996944,1716374,1982735,3615225,
4486806,3037122,17,54,55,210,312,358,857,350,7368,8443,6286,1750,7367,14092,
28954,80779,176893,354939,446792,33333,69911,53144,29169,18005,11704,13363,
18028,46547,14574,8954,2483,14693,25467,25215,41254,46237,98263,185986),
.Dim=c(19,5),.Dimnames=list(c("1820-30","1831-40","1841-50","1851-60","1861-70",
"1871-80","1881-90","1891-00","1901-10","1911-20",
"1921-30","1931-40","1941-50","1951-60","1961-70",
"1971-80","1981-90","1991-00","2001-06"),
c("Europe","Asia","Americas","Africa","Oceania")))
df.m <- melt(df)
df.m <- rename(df.m, Period = Var1, Region = Var2)
output$chart <- renderPlotly({
plot_ly(data = df.m, x = Period, y = value/1e+06, color = Region, type = "bar", source = "select") %>%
layout(title = "Migration to the United States by Source Region (1820-2006), In Millions",
xaxis = list(type = "category"),
barmode = "stack")
})
output$DToutput <- DT::renderDataTable({
datatable(df.m, selection = list(target = "row+column"),
options = list(pageLength = nrow(df.m), dom = "ft"))
})
proxy = dataTableProxy('DToutput')
# highlight rows that are selected on plotly output
observe({
event.data = plotly::event_data("plotly_click", source = "select")
if(is.null(event.data)) {
rowNums <- NULL
} else {
rowNums <- row.names(df.m[df.m$Period %in% event.data$x,])
}
proxy %>% selectRows(as.numeric(rowNums))
})
})
I am new to Shiny/ggvis and I want to create a scatter plot that allows the user to select from an X and Y dropdown. I have attempted this feat may times to no avail and would greatly appreciate some help. Please see the code below.
library(shiny)
library(ggvis)
library(dplyr)
# Define the user interface
shinyUI(pageWithSidebar(
# Add a title to this page
headerPanel(
h1("Test the Header Panel!")),
sidebarPanel(
uiOutput("ggvis_ui"),
sliderInput(inputId = "size",label = "Area",10, 1000, value = c(10)),
selectInput(inputId = "yAxis",label = "Y variable", c("wt","drat")),
selectInput(inputId = "xAxis",label = " X variable", c("cyl", "am","gear"))),
mainPanel(
h1("Please review the chart below showing nothing!"),
ggvisOutput("ggvis")
)
)
)
Server.r
# Create server.R
shinyServer(function(input, output, session) {
# A reactive expression wrapper for input$size
input_size <- reactive(input$size)
input_xAxis <- reactive(input$xAxis)
input_yAxis <- reactive(input$yAxis)
# A reactive expression wrapper for input$size
mtcars %>%
ggvis(x =input_xAxis, y = input_yAxis, size := input_size) %>%
layer_points() %>%
bind_shiny("ggvis", "ggvis_ui")
})
The two things you are missing is making the plot reactive and using prop for setting properties when the variables names are strings.
The following change to the server code returns a reactive graphic:
plot = reactive({
mtcars %>%
ggvis(prop("x", as.name(input_xAxis())),
prop("y", as.name(input_yAxis())),
size := input_size) %>%
layer_points()
})
plot %>%
bind_shiny("ggvis", "ggvis_ui")