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app.R
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app.R
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## Developed by:
## Michael Thomas
## Chief Data Scientist
## Ketchbrook Analytics
## Contact: [email protected]
library(shiny)
library(shinythemes) # simple way to use bootstrap UI theme
library(emo) # emojis (for app header)
library(arrow) # read data from parquet
library(dplyr) # ETL
library(reactable) # interactive data tables
library(waiter) # custom loading screens
data <- arrow::read_parquet(
file = here::here("data/all_of_the_data.parquet"),
as_data_frame = FALSE # keep as parquet table to keep back-end lighter
)
# Build the front-end UI
ui <- shiny::navbarPage(
title = paste0("{arrow} + {shiny} ", emo::ji(keyword = "heart")),
theme = shinythemes::shinytheme(theme = "cerulean"),
shiny::tabPanel(
title = "Home",
waiter::use_waiter(),
shiny::fluidRow(
shiny::column(
width = 4,
shiny::wellPanel(
# Create a UI drop-down menu...
shiny::selectizeInput(
inputId = "choose_item_code",
label = paste0("Select an \"Item Code\" to View Related Data"),
choices = NULL,
selected = character(0),
options = list(
placeholder = "Choose One...",
onInitialize = I('function() { this.setValue(""); }')
)
),
shiny::br(),
shiny::div(
class = "float-right",
shiny::actionButton(
inputId = "apply_item_code_btn",
class = "float-right",
label = "Apply"
)
)
)
),
shiny::column(
width = 8,
shiny::wellPanel(
shiny::h4("How it works:"),
shiny::p(
paste0(
"The back-end dataset behind this app consists of 2 million rows ",
"of data across 11 variables. The 'Item_Code' variable contains ",
"1,000 unique alphanumeric codes, which must be individually ",
"selected to view the related (filtered) data."
)
),
shiny::p(
paste0(
"When the user selects an Item Code and clicks \"Apply\", that ",
"Item Code is sent to the server to be used to generate a ",
"reactive data frame via "
)
),
shiny::code("dplyr::filter(Item_Code == [Selected Item Code])"),
shiny::br(),
shiny::br(),
shiny::a(
href = "https://github.com/mthomas-ketchbrook/shiny_arrow/blob/main/app.R",
target = "_blank",
"Browse App Source Code"
)
)
)
),
shiny::hr(),
shiny::fluidRow(
shiny::column(
width = 12,
reactable::reactableOutput(
outputId = "tbl"
)
)
)
),
shiny::tabPanel(
title = "About",
shiny::fluidRow(
shiny::column(
width = 12,
shiny::div(
class = "jumbotron",
shiny::h1("Curious to Learn More?"),
shiny::p(
class = "lead",
"Check out what else we do at Ketchbrook Analytics."
),
shiny::a(
class = "btn btn-info btn-lg",
href = "https://www.ketchbrookanalytics.com/",
target = "_blank",
"Visit Us"
)
)
)
)
)
)
# Build the back-end Server
server <- function(input, output, session) {
# Build loading screen
w <- waiter::Waiter$new(
html = shiny::tagList(
"Querying Data...",
waiter::spin_ball()
)
)
# Initiate a 'reactiveValues' object
rctv <- shiny::reactiveValues()
# Start off with no Item Code selected
rctv$selected_item_code <- NULL
# Set up the 'selectizeInput' drop-down choices on the server-side; this is
# done to improve performance,
# RE: https://shiny.rstudio.com/articles/selectize.html
shiny::updateSelectizeInput(
session = session,
inputId = "choose_item_code",
choices = data %>%
dplyr::select(Item_Code) %>%
dplyr::collect() %>%
dplyr::pull(Item_Code) %>%
unique() %>%
sort(),
selected = character(0),
options = list(
placeholder = "Choose One...",
render = I('function() { this.setValue(""); }')
),
server = TRUE
)
# When an Item Code is selected...
shiny::observeEvent(input$apply_item_code_btn, {
# Require that a valid Item Code has been selected
shiny::req(input$choose_item_code != "")
w$show()
Sys.sleep(1)
rctv$selected_item_code <- input$choose_item_code
# Capture the filtered data based upon the UI selection
rctv$filtered_data <- data %>%
dplyr::filter(Item_Code == rctv$selected_item_code) %>%
dplyr::collect() # convert from parquet table to tibble, so that we can
# use the selected data downstream in a plot/table/etc.
})
# TODO: build a ggplot or something to display the selected observations
# Build an interactive data table using the 'filtered_data' data frame
output$tbl <- reactable::renderReactable({
shiny::req(rctv$filtered_data)
tbl <- reactable::reactable(
data = rctv$filtered_data %>%
dplyr::relocate(
Item_Code,
.before = tidyselect::everything()
),
defaultColDef = reactable::colDef(
cell = function(value) {
round(value, 3)
}
),
columns = list(
Item_Code = reactable::colDef(
align = "center",
cell = function(value) {
value
}
)
)
)
w$hide()
return(tbl)
})
}
shinyApp(ui, server)