Update app.R

app.R

@@ -1,51 +1,129 @@
 library(shiny)
+library(shinyalert)
+library(shinythemes)
+library(shinycssloaders)
+library(shinyjs)
+library(httr)
 library(bslib)
+library(thematic)
+library(gtrendsR)
+library(plotly)
 library(dplyr)
 library(ggplot2)
 
-df <- readr::read_csv("penguins.csv")
-# Find subset of columns that are suitable for scatter plot
-df_num <- df |> select(where(is.numeric), -Year)
-
-ui <- page_fillable(theme = bs_theme(bootswatch = "minty"),
-  layout_sidebar(fillable = TRUE,
-    sidebar(
-      varSelectInput("xvar", "X variable", df_num, selected = "Bill Length (mm)"),
-      varSelectInput("yvar", "Y variable", df_num, selected = "Bill Depth (mm)"),
-      checkboxGroupInput("species", "Filter by species",
-        choices = unique(df$Species), selected = unique(df$Species)
-      ),
-      hr(), # Add a horizontal rule
-      checkboxInput("by_species", "Show species", TRUE),
-      checkboxInput("show_margins", "Show marginal plots", TRUE),
-      checkboxInput("smooth", "Add smoother"),
-    ),
-    plotOutput("scatter")
-  )
+options(spinner.color = "lightblue",
+        spinner.color.background = "#ffffff",
+        spinner.size = 2)
+
+my_theme <- bs_theme(
+    bg = "#fdfefe",
+    fg = "blue",
+    primary = "red",
+    base_font = font_google("PT Sans Caption"),
+    "font-size-base" = "0.9rem",
+    version = 5,
+    "navbar-bg" = "blue"
 )
 
-server <- function(input, output, session) {
-  subsetted <- reactive({
-    req(input$species)
-    df |> filter(Species %in% input$species)
-  })
+thematic_shiny()
+
+ui <- list(useShinyjs(),navbarPage(windowTitle = "TrendChecker",
+                                   title = strong("TrendChecker"),theme = my_theme,
+                                   tabPanel(title = strong("Trend Over Time"),icon = icon("chart-line"),
+                                            sidebarLayout(
+                                                sidebarPanel(width = 3,actionButton("info",strong("About TrendChecker",icon("info"))),hr(),
+                                                             hidden(tags$div(id = "about",h5("TrendChecker is a web application that enables users to monitor the search popularity of any subject of interest over time,
+                                                                                          and across different countries by calling the Google trend api. Search hit of 100 is the indicator of optimum popularity, while other hits are measured relative to the optimum."))),h4(strong("Controls")),hr(),
+                                                             textInput("text",strong("Enter Search Term"),value = "Soccer"),
+                                                             checkboxGroupInput("check",strong("Select Country(ies)"),choices = c("USA" = "US","UK" = "GB","Germany" = "DE","Netherlands" = "NL","Nigeria" = "NG","Japan" = "JP"),selected = "US"),
+                                                             radioButtons("radio",strong("Choose Trend Source"),choices = c("Web","News","YouTube","Images"),selected = "News"),
+                                                             radioButtons("time",strong("Select Time Frame"),choices = c("Last Hour","Last Four Hours","Last Day","Last Seven Days","Past 30 Days","Past 90 Days","Past 12 Months","Last Five Years"),selected = "Last Seven Days"),
+                                                             actionButton("run",strong("Run Query"),icon("caret-right"))
+                                                             ),
+                                                mainPanel(
+                                                          withSpinner(plotlyOutput("plot"),type = 8))
+                                                          
+                                            ))
+)) 
+
+# Define server logic required to run query
+
+server <- function(input, output,session) {
   
-  output$scatter <- renderPlot({
-    p <- ggplot(subsetted(), aes(!!input$xvar, !!input$yvar)) + list(
-      theme(legend.position = "bottom"),
-      if (input$by_species) aes(color=Species),
-      geom_point(),
-      if (input$smooth) geom_smooth()
-    )
-
-    if (input$show_margins) {
-      margin_type <- if (input$by_species) "density" else "histogram"
-      p <- p |> ggExtra::ggMarginal(type = margin_type, margins = "both",
-        size = 8, groupColour = input$by_species, groupFill = input$by_species)
-    }
-    
-    p
-  }, res = 100)
+## APP info button toggle activation
+    
+observeEvent(input$info,{
+    toggle("about")
+})    
+
+
+## Create reactive input switch functionality
+    
+check_input <- reactive(input$check)
+    
+
+radio_input <- reactive(switch(input$radio,
+                      "Web" = "web",
+                      "News" = "news",
+                      "YouTube" = "youtube",
+                      "Images" = "images"))
+
+radio_time <- reactive(switch(input$time,
+                     "Last Hour" = "now 1-H",
+                     "Last Four Hours" = "now 4-H",
+                     "Last Day" = "now 1-d",
+                     "Last Seven Days" = "now 7-d",
+                     "Past 30 Days" = "today 1-m",
+                     "Past 90 Days" = "today 3-m",
+                     "Past 12 Months" = "today 12-m",
+                     "Last Five Years" = "today+5-y"))
+
+
+    
+text_input <- reactive(input$text)
+
+
+
+
+## Write the trend function
+
+trend <- function(){
+    
+    gt <- gtrends(keyword = c(text_input()),geo = c(check_input()),gprop = radio_input(),
+            time = radio_time())
+    
+    p <- plot(gt)
+    
+    gp <- ggplotly(p)
+    
+    return(gp)
+}
+    
+## Convert to reactive function
+
+trend2 <- reactive(trend())
+
+## Create interactive plot
+
+output$plot <- renderPlotly({
+    
+    withProgress(message = "Fetching data",
+                 detail = "This may take a while...",value = 0,{
+                     
+                     for (i in 1:25){
+                         
+                         incProgress(1/25)
+                         Sys.sleep(0.25)
+                     }
+                 })    
+    
+    input$run
+    isolate(trend2())
+    
+
+})
+       
 }
 
-shinyApp(ui, server)
+# Run the application 
+shinyApp(ui = ui, server = server)