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MAT381E-Fall21 · Jan 9, 2022 · 21ab2be · 21ab2be
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diff --git a/.DS_Store b/.DS_Store
diff --git a/app.R b/app.R
@@ -0,0 +1,48 @@
+library(shiny)
+
+# Define UI for application that draws a histogram
+ui <- fluidPage(
+
+  ## Main header
+  tags$h1("My First Shiny App"),
+
+  tags$p(" I love data science."),
+
+  ## Un-ordered list
+
+  tags$ul(
+    tags$li("Tidyverse"), 
+    tags$li("Rvest"), 
+    tags$li("Shiny")
+  ),
+
+
+  ## Tags can be nested.
+
+  tags$p(
+    "The link to the Shiny website is",
+    tags$a(href = "https://www.rstudio.com/shiny/", "rstudio.com/shiny."),
+    tags$strong("I strongly recommend that you take a look at it!")
+  ),
+
+  ## Some line break.
+  tags$br(),
+
+  ## Include video.
+
+  tags$iframe(src="https://www.youtube.com/embed/xJALSnbBHhk", width="1000", height="500",
+              frameborder="0", 
+              allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"),
+
+  tags$br(),
+
+  tags$span(style="color:purple", "Have a good winter break!..")
+)
+
+# Define server logic required to draw a histogram
+server <- function(input, output) {
+
+}
+
+# Run the application 
+shinyApp(ui = ui, server = server)
diff --git a/countries-01/app.R b/countries-01/app.R
@@ -14,19 +14,22 @@ countries_data_2011 <- countries_data %>%
 ## UI ##########################################################################
 ui <- fluidPage(
 
-    sidebarLayout(#position = "right",
+    sidebarLayout(#position = "right", #default widget position is left
 
         ## define inputs in sidebar -------------------------------
         sidebarPanel(
 
-            ## select variable for scatter plot x-axis --------------
-            ## label: widget label.  
+            ##select variable widget for scatter plot x-axis --------------
+            #inputId: The input slot that will be used to access the value.	
+            #label:	Display label for the control, or NULL for no label.
+            #choices:	List of values to select from. column names from the data set.
+            #selected: The initially selected value.	
             selectInput(inputId = "x_axis", label = "X axis",
                         choices = c("human_development_index", "corruption_perception_index",
                                     "population", "life_exp", "gdp_per_capita"),
                         selected = "human_development_index"),
 
-            ## select variable for scatter plot y-axis ---------------
+            ##select variable widget for scatter plot y-axis --------------
             selectInput(inputId = "y_axis", label = "Y axis",
                         choices = c("human_development_index", "corruption_perception_index",
                                     "population", "life_exp", "gdp_per_capita"),
@@ -47,7 +50,7 @@ server <- function(input, output) {
 
     ## input and output are list-type objects. list elements will be named by me.
     ## create a scatter plot.
-    ## output is a reserved word.
+    ## input and output are reserved words.
     ## countries_scatter is given by me.
     ## input has two parts: x_axis and y_axis
     ## renderPlot({expr}): Renders a reactive plot that is suitable for assigning to an output plot.

diff --git a/countries-02/app.R b/countries-02/app.R
@@ -20,7 +20,6 @@ ui <- fluidPage(
         sidebarPanel(
 
             ## select variable for scatter plot x-axis --------------
-            ## label: widget label.  
             selectInput(inputId = "x_axis", label = "X axis",
                         choices = c("human_development_index", "corruption_perception_index",
                                     "population", "life_exp", "gdp_per_capita"),

diff --git a/countries-03/app.R b/countries-03/app.R
@@ -19,7 +19,6 @@ ui <- fluidPage(
         sidebarPanel(
 
             ## select variable for scatter plot x-axis --------------
-            ## label: widget label.  
             selectInput(inputId = "x_axis", label = "X axis",
                         choices = c("human_development_index", "corruption_perception_index",
                                     "population", "life_exp", "gdp_per_capita"),
@@ -37,8 +36,13 @@ ui <- fluidPage(
                         selected = "population"),
 
             ## set transparency level for points in the scatter plot ----------------
-            sliderInput(inputId ="transvalue", label = "Transparency", 
-                         min = 0, max = 1, value = 0.8) 
+            ## inputId: The input slot that will be used to access the value.
+            ## label: Display label for the control,
+            ## min, max: The minimum and maximum values (inclusive) that can be selected.
+            ## value:The initial value of the slider
+            sliderInput(inputId ="transvalue", 
+                        label = "Transparency", 
+                        min = 0, max = 1, value = 0.8) 
 
         ),
 
@@ -58,7 +62,7 @@ server <- function(input, output) {
         ggplot(data = countries_data_2011, 
                aes_string(x = input$x_axis, y = input$y_axis)) +
             geom_point(aes_string(color="continent", size=input$size), alpha = input$transvalue) +
-            #note that i am directly changing the characteristics of point. it is out of aes(). 
+            #note that i am mapping the alpha size onto a variable. for that reason it is out of aes(). 
             #i mean its value does not depend on a variable, that is why it is out of aes().
             theme_minimal()
     })

diff --git a/countries-04/app.R b/countries-04/app.R
@@ -20,7 +20,7 @@ ui <- fluidPage(
         sidebarPanel(
 
             ## select variable for scatter plot x-axis --------------
-            ## label: widget label.  
+
             selectInput(inputId = "x_axis", label = "X axis",
                         choices = c("human_development_index", "corruption_perception_index",
                                     "population", "life_exp", "gdp_per_capita"),

diff --git a/countries-05/app.R b/countries-05/app.R
@@ -20,7 +20,7 @@ ui <- fluidPage(
         sidebarPanel(
 
             ## select variable for scatter plot x-axis --------------
-            ## label: widget label.  
+
             selectInput(inputId = "x_axis", label = "X axis",
                         choices = c("human_development_index", "corruption_perception_index",
                                     "population", "life_exp", "gdp_per_capita"),
@@ -42,6 +42,9 @@ ui <- fluidPage(
                         min = 0, max = 1, value = 0.8),
 
             ## checkbox to show/hide data table -------------------
+            ## inputId: The input slot that will be used to access the value.	
+            ## label: Display label for the control, or NULL for no label.
+            ## value: Initial value (TRUE or FALSE).
             checkboxInput(inputId = "show_table", label = "Show table",
                           value = TRUE)
 

diff --git a/countries-06/app.R b/countries-06/app.R
@@ -24,7 +24,7 @@ ui <- fluidPage(
         sidebarPanel(
 
             ## select variable for scatter plot x-axis --------------
-            ## label: widget label.  
+
             selectInput(inputId = "x_axis", label = "X axis",
                         choices = c("human_development_index", "corruption_perception_index",
                                     "population", "life_exp", "gdp_per_capita"),
@@ -72,13 +72,14 @@ server <- function(input, output) {
 #https://stackoverflow.com/questions/37663854/convert-ggplot-object-to-plotly-in-shiny-application
     output$countries_scatter <- renderPlotly({
 
-        ggplotly(ggplot(data = countries_data_2011, 
-                     aes_string(x = input$x_axis, y = input$y_axis)) +
-                     geom_point(aes_string(color="continent", size=input$size),
-                     alpha = input$transvalue) + 
-                     theme_minimal()) 
-
+
+      p_scatter <- ggplot(data = countries_data_2011, 
+                          aes_string(x = input$x_axis, y = input$y_axis)) +
+                   geom_point(aes_string(color="continent", size=input$size),
+                             alpha = input$transvalue) + 
+                   theme_minimal()
 
+      ggplotly(p_scatter)
 
     })
 

diff --git a/countries-07/app.R b/countries-07/app.R
@@ -2,6 +2,7 @@
 library(shiny)
 library(tidyverse)
 library(plotly)
+library(DT)
 
 ## read data -------------------------------------------------------------------
 
@@ -59,7 +60,7 @@ ui <- fluidPage(
 
             plotlyOutput(outputId = "countries_scatter"),
 
-            dataTableOutput(outputId = "countries_table")
+           dataTableOutput(outputId = "countries_table")
         )
     )
 )
@@ -85,17 +86,15 @@ server <- function(input, output) {
                                        size = input$point_size,
                                        label = "country"))+
             geom_point(alpha = input$transvalue)+
-            theme_minimal()+
-            labs(title = input$year)
+            theme_minimal()
 
         ggplotly(p_scatter)
     })
 
     ## create data table -------------------------------------
     output$countries_table <- renderDataTable({
-        if(input$show_table){
-            datatable(countries_subset(), rownames = FALSE) ###pay attention:countries_subset()
-        }
+        if(input$show_table){countries_subset()}
+
     })
 }
 

diff --git a/countries-08/app.R b/countries-08/app.R
@@ -72,7 +72,7 @@ server <- function(input, output) {
 
     ## calculate summaries per continent -----------------
     countries_summary <- reactive({
-        countries_subset() %>%      ###pay attention:countries_subset() 
+        countries_subset() %>%      ###pay attention:countries_subset() #treats as a function. return is function.
             group_by(continent) %>% 
             summarise(gdp_median = median(gdp_per_capita, na.rm = TRUE) %>% round(2),
                       life_exp_median = median(life_exp, na.rm = TRUE) %>% round(2))
@@ -88,18 +88,16 @@ server <- function(input, output) {
                                        size = input$point_size,
                                        label = "country"))+
             geom_point(alpha = input$transvalue)+
-            theme_minimal()+
-            labs(title = input$year)
+            theme_minimal()
 
         ggplotly(p_scatter)
     })
 
 
     ## create data table -------------------------------------
     output$countries_table <- renderDataTable({
-        if(input$show_table){
-            datatable(countries_summary(), rownames = FALSE)  ###pay attention:countries_summary() 
-        }
+        if(input$show_table){countries_summary()} ###pay attention:countries_summary() 
+
     })
 }
 

diff --git a/countries-09/app.R b/countries-09/app.R
@@ -67,11 +67,11 @@ ui <- fluidPage(#theme = shinytheme("superhero"),
         mainPanel(
 
             ## show output in multiple tabs ----------------
-            tabsetPanel(type = "tabs",
-                        tabPanel(title = "Plot",
+            tabsetPanel(type = "tabs", #standard look
+                        tabPanel(title = "Plot", #display title for the tab
                                  plotlyOutput(outputId = "countries_scatter")),
                         tabPanel(title = "Data",
-                                 DT::dataTableOutput(outputId = "countries_table"))
+                                 dataTableOutput(outputId = "countries_table"))
 
             )
 
@@ -107,18 +107,16 @@ server <- function(input, output) {
                                        size = input$point_size,
                                        label = "country"))+
             geom_point(alpha = input$transvalue)+
-            theme_minimal()+
-            labs(title = input$year)
+            theme_minimal()
 
         ggplotly(p_scatter)
     })
 
 
     ## create data table -------------------------------------
     output$countries_table <- renderDataTable({
-        if(input$show_table){
-            datatable(countries_summary(), rownames = FALSE)  ###pay attention:countries_summary() 
-        }
+        if(input$show_table){countries_summary()} ###pay attention:countries_summary()
+
     })
 }
 

diff --git a/deneme3/app.R b/deneme3/app.R
@@ -0,0 +1,49 @@
+#
+# This is a Shiny web application. You can run the application by clicking
+# the 'Run App' button above.
+#
+# Find out more about building applications with Shiny here:
+#
+#    http://shiny.rstudio.com/
+#
+
+library(shiny)
+
+# Define UI for application that draws a histogram
+ui <- fluidPage(
+
+    # Application title
+    titlePanel("Old Faithful Geyser Data"),
+
+    # Sidebar with a slider input for number of bins 
+    sidebarLayout(
+        sidebarPanel(
+            sliderInput("bins",
+                        "Number of bins:",
+                        min = 1,
+                        max = 50,
+                        value = 30)
+        ),
+
+        # Show a plot of the generated distribution
+        mainPanel(
+           plotOutput("distPlot")
+        )
+    )
+)
+
+# Define server logic required to draw a histogram
+server <- function(input, output) {
+
+    output$distPlot <- renderPlot({
+        # generate bins based on input$bins from ui.R
+        x    <- faithful[, 2]
+        bins <- seq(min(x), max(x), length.out = input$bins + 1)
+
+        # draw the histogram with the specified number of bins
+        hist(x, breaks = bins, col = 'darkgray', border = 'white')
+    })
+}
+
+# Run the application 
+shinyApp(ui = ui, server = server)
diff --git a/images/subset_reactive.png b/images/subset_reactive.png