my_server.R

source('wrangle3.R')
source('wrangle4.R')
source('wrangle2.R')

my_server <- function(input, output) {
  
  output$q1_page <- renderPrint({
    filename <- input$q1_select
    filename <- sub('Introduction', 'intro', filename)
    filename <- sub('Computer Science', 'cs', filename)
    filename <- sub('Business', 'bu', filename)
    filename <- sub('Conclusion', 'conc', filename)
    
    includeHTML(paste0('./www/pages/', filename, '.html'))
  })
  
  output$q1_subsec <- renderPrint({
    filename <- input$q1_select
    filename <- sub('Computer Science', 'cs', filename)
    filename <- sub('Business', 'bu', filename)
    
    type <- input$q1_type
    type <- substr(type, nchar(type), nchar(type))
    
    includeHTML(paste0('./www/pages/', filename, type, '.html'))
  })

      # Renders a plot with the selected years in the x axis and the area in the y axis
  #if(input$school_select_high == "University of Washington") {

  output$uw_high <- renderPlot ({
    
    uw_high_plot <- ggplot(data = uw_distinct_high) +
      geom_col(mapping = aes(x = Department, y = `Number of Classes`), fill = "#8856a7") +
      labs(
        title = "Departments at UW with High Class GPAs (GPA >= 3.8)", 
        x = "Departments", 
        y = "Number of Classes"
      ) +
      theme(plot.title = element_text(hjust = 0.5)) 
    uw_high_plot
  })
 # } else {
  output$vt_high <- renderPlot ({
    
    vt_high_plot <- ggplot(data = vt_distinct_high) +
      geom_col(mapping = aes(x = Department, y = `Number of Classes`), fill = "#99000d") +
      labs(
        title = "Departments at VT with High Class GPAs (GPA >= 3.8)", 
        x = "Departments", 
        y = "Number of Classes"
      ) +
      theme(plot.title = element_text(hjust = 0.5)) 
    vt_high_plot
  })
#}
  output$uw_low <- renderPlot ({
    
    uw_low_plot <- ggplot(data = uw_distinct_low) +
      geom_col(mapping = aes(x = Department, y = `Number of Classes`), fill = "#8856a7") +
      labs(
        title = "Departments at UW with High Class GPAs (GPA <= 2.8)", 
        x = "Departments", 
        y = "Number of Classes"
      ) + 
      theme(plot.title = element_text(hjust = 0.5)) 
    uw_low_plot
  })
  output$vt_low <- renderPlot ({
    
    vt_low_plot <- ggplot(data = vt_distinct_low) +
      geom_col(mapping = aes(x = Department, y = `Number of Classes`), fill = "#99000d") +
      labs(
        title = "Departments at VT with High Class GPAs (GPA <= 2.8)", 
        x = "Departments", 
        y = "Number of Classes"
      ) +
      theme(plot.title = element_text(hjust = 0.5)) 
    vt_low_plot
  })
  
  output$q4plot <- renderPlot({
    if (input$subject == "Math"){
      uw_summary <- uw %>% 
        filter(Subject %in% c("MATH", "AMAT", "STAT")) %>% 
        group_by(Size) %>% 
        summarize( Average_GPA = mean(Average_GPA)) %>% 
        mutate(School = "University of Washington")
      
      vt_summary <- virginia_tech %>% 
        filter(Subject %in% c("MATH", "STAT")) %>%
        group_by(Size) %>% 
        summarize( Average_GPA = mean(Average_GPA)) %>% 
        mutate(School = "Virginia Tech")
    } else if (input$subject == "Science"){
      uw_summary <- uw %>% 
        filter(Subject %in% c("BIOL", "CHEM", "PHYS")) %>% 
        group_by(Size) %>% 
        summarize( Average_GPA = mean(Average_GPA)) %>% 
        mutate(School = "University of Washington")
      
      vt_summary <- virginia_tech %>% 
        filter(Subject %in% c("BIOL", "CHEM", "PHYS")) %>%
        group_by(Size) %>% 
        summarize( Average_GPA = mean(Average_GPA)) %>% 
        mutate(School = "Virginia Tech")
    } else if (input$subject == "English"){
      uw_summary <- uw %>% 
        filter(Subject == "ENGL") %>% 
        group_by(Size) %>% 
        summarize( Average_GPA = mean(Average_GPA)) %>% 
        mutate(School = "University of Washington")
      
      vt_summary <- virginia_tech %>% 
        filter(Subject == "ENGL") %>%
        group_by(Size) %>% 
        summarize( Average_GPA = mean(Average_GPA)) %>% 
        mutate(School = "Virginia Tech")
    } else if (input$subject == "Social Science"){
      uw_summary <- uw %>% 
        filter(Subject %in% c("COM ", "SOC ", "PSYC")) %>% 
        group_by(Size) %>% 
        summarize( Average_GPA = mean(Average_GPA)) %>% 
        mutate(School = "University of Washington")
      
      vt_summary <- virginia_tech %>% 
        filter(Subject %in% c("COMM", "SOC ", "PSYC")) %>%
        group_by(Size) %>% 
        summarize( Average_GPA = mean(Average_GPA)) %>% 
        mutate(School = "Virginia Tech")
    } else {
      uw_summary <- uw %>% 
        group_by(Size) %>% 
        summarize( Average_GPA = mean(Average_GPA)) %>% 
        mutate(School = "University of Washington")
      
      vt_summary <- virginia_tech %>% 
        group_by(Size) %>% 
        summarize( Average_GPA = mean(Average_GPA)) %>% 
        mutate(School = "Virginia Tech")
    }
    
    combined_data <- full_join(uw_summary, vt_summary, by = c("Size", "Average_GPA", "School"))
    
    positions <- c("Less than 25", "25-50", "Greater than 50")
    ggplot(data = combined_data, aes(x = Size, y = Average_GPA, fill = School)) + 
      geom_bar(stat="identity", position=position_dodge()) +
      scale_x_discrete(limits = positions) +
      scale_fill_manual(values = c('#8856a7','#99000d')) +
      labs(title = paste0("GPA Based on Class Size for ", input$subject), y = "Average GPA") +
      theme(plot.title = element_text(hjust = 0.5)) 
  })
  
  output$uw_graph_q3 <- renderPlot({
    uw_graph <- ggplot(summary_uw_grades,
      mapping = aes(
        x = Subject,
        y = avg_gpa,
        fill = teaches_multiple
      )
    ) +
      geom_col(position = "dodge") +
      labs(
        title = "University of Washington Average Subjectal Grades for
          Professors Teaching a Single Course vs Multiple Courses",
        x = "Subject",
        y = "Grade Point Average",
        fill = "Teaches Multiple Courses"
      ) +
      scale_x_discrete(labels = c(
        "Biology", "Chemistry", "Computer Science",
        "Informatics", "Math", "Physics"
      )) +
      scale_fill_manual(values = c("#8856a7", "gold"))
    uw_graph
  })

  output$vt_graph_q3 <- renderPlot({
    vt_graph <- ggplot(summary_vt_grades,
      mapping = aes(
        x = Subject,
        y = avg_gpa,
        fill = teaches_multiple
      )
    ) +
      geom_col(position = "dodge") +
      labs(
        title = "Virginia Tech Average Subject Grades for Professors
      Teaching a Single Course vs Multiple Courses",
        x = "Subject",
        y = "Grade Point Average",
        fill = "Teaches Multiple Courses"
      ) +
      scale_x_discrete(labels = c(
        "Biology", "Chemistry", "Computer Science",
        "Math", "Physics"
      )) +
      scale_fill_manual(values = c("#99000d", "#E87722"))
    vt_graph
  })
  
}