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library(shiny)
library(plotly)
library(dplyr)
data(sales, package = "plotlyBook")
categories <- unique(sales$category)
sub_categories <- unique(sales$sub_category)
ids <- unique(sales$id)
ui <- fluidPage(
uiOutput("history"),
plotlyOutput("bars", height = 200),
plotlyOutput("lines", height = 300)
)
server <- function(input, output, session) {
# These reactive values keep track of the drilldown state
# (NULL means inactive)
drills <- reactiveValues(
category = NULL,
sub_category = NULL,
id = NULL
)
# filter the data based on active drill-downs
# also create a column, value, which keeps track of which
# variable we're interested in
sales_data <- reactive({
if (!length(drills$category)) {
return(mutate(sales, value = category))
}
sales <- filter(sales, category %in% drills$category)
if (!length(drills$sub_category)) {
return(mutate(sales, value = sub_category))
}
sales <- filter(sales, sub_category %in% drills$sub_category)
mutate(sales, value = id)
})
# bar chart of sales by 'current level of category'
output$bars <- renderPlotly({
d <- count(sales_data(), value, wt = sales)
p <- plot_ly(d, x = ~value, y = ~n, source = "bars") %>%
layout(
yaxis = list(title = "Total Sales"),
xaxis = list(title = "")
)
if (!length(drills$sub_category)) {
add_bars(p, color = ~value)
} else if (!length(drills$id)) {
add_bars(p) %>%
layout(
hovermode = "x",
xaxis = list(showticklabels = FALSE)
)
} else {
# add a visual cue of which ID is selected
add_bars(p) %>%
filter(value %in% drills$id) %>%
add_bars(color = I("black")) %>%
layout(
hovermode = "x", xaxis = list(showticklabels = FALSE),
showlegend = FALSE, barmode = "overlay"
)
}
})
# time-series chart of the sales
output$lines <- renderPlotly({
p <- if (!length(drills$sub_category)) {
sales_data() %>%
count(order_date, value, wt = sales) %>%
plot_ly(x = ~order_date, y = ~n) %>%
add_lines(color = ~value)
} else if (!length(drills$id)) {
sales_data() %>%
count(order_date, wt = sales) %>%
plot_ly(x = ~order_date, y = ~n) %>%
add_lines()
} else {
sales_data() %>%
filter(id %in% drills$id) %>%
select(-value) %>%
plot_ly() %>%
add_table()
}
p %>%
layout(
yaxis = list(title = "Total Sales"),
xaxis = list(title = "")
)
})
# control the state of the drilldown by clicking the bar graph
observeEvent(event_data("plotly_click", source = "bars"), {
x <- event_data("plotly_click", source = "bars")$x
if (!length(x)) return()
if (!length(drills$category)) {
drills$category <- x
} else if (!length(drills$sub_category)) {
drills$sub_category <- x
} else {
drills$id <- x
}
})
# populate a `selectInput()` for each active drilldown
output$history <- renderUI({
if (!length(drills$category)) return("Click the bar chart to drilldown")
categoryInput <- selectInput(
"category", "Category",
choices = categories, selected = drills$category
)
if (!length(drills$sub_category)) return(categoryInput)
sd <- filter(sales, category %in% drills$category)
subCategoryInput <- selectInput(
"sub_category", "Sub-category",
choices = unique(sd$sub_category),
selected = drills$sub_category
)
if (!length(drills$id)) {
return(fluidRow(
column(3, categoryInput),
column(3, subCategoryInput)
))
}
sd <- filter(sd, sub_category %in% drills$sub_category)
idInput <- selectInput(
"id", "Product ID",
choices = unique(sd$id), selected = drills$id
)
fluidRow(
column(3, categoryInput),
column(3, subCategoryInput),
column(3, idInput)
)
})
# control the state of the drilldown via the `selectInput()`s
observeEvent(input$category, {
drills$category <- input$category
drills$sub_category <- NULL
drills$id <- NULL
})
observeEvent(input$sub_category, {
drills$sub_category <- input$sub_category
drills$id <- NULL
})
observeEvent(input$id, {
drills$id <- input$id
})
}
shinyApp(ui, server)
|
