LA

Installing Required Package

This step installs the shiny package, which is used to build interactive dashboards in R.

##install.packages("shiny")

Load Libraries

All required libraries are loaded. These libraries provide functions for dashboard design, data handling, and visualization.

library(shiny)

Warning: package 'shiny' was built under R version 4.5.3

library(shinydashboard)

Warning: package 'shinydashboard' was built under R version 4.5.3

Attaching package: 'shinydashboard'

The following object is masked from 'package:graphics':

    box

library(ggplot2)

Warning: package 'ggplot2' was built under R version 4.5.3

library(dplyr)

Warning: package 'dplyr' was built under R version 4.5.3

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

library(plotly)

Warning: package 'plotly' was built under R version 4.5.3

Attaching package: 'plotly'

The following object is masked from 'package:ggplot2':

    last_plot

The following object is masked from 'package:stats':

    filter

The following object is masked from 'package:graphics':

    layout

Data Loading

The dataset is loaded from a CSV file stored locally on the system.

data <- read.csv("Covid_data.csv")

This dataset contains COVID-19 information such as country, cases, and deaths.

Data Cleaning

The date column is converted into Date format so it can be used for time-based filtering and plotting.

data$date <- as.Date(data$date)

User Interface (UI): Header

The dashboard header displays the title of the application.

dashboardHeader(title = "COVID-19 Dashboard")

COVID-19 Dashboard

Toggle navigation

User Interface (UI): Sidebar Inputs

The sidebar contains input controls for user interaction.

selectInput: Allows user to select a country dateRangeInput: Allows user to filter data by date

dashboardSidebar(
  selectInput("country", "Select Country:",
              choices = unique(data$country),
              selected = unique(data$country)[1]),
  
  dateRangeInput("dateRange",
                 "Select Date Range:",
                 start = min(data$date),
                 end = max(data$date))
)

Select Country:

Afghanistan Albania Algeria Andorra Angola Anguilla Antigua And Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia And Herzegovina Botswana Brazil British Virgin Islands Brunei Darussalam Bulgaria Burkina Faso Burundi Cabo Verde Cambodia Cameroon Canada Caribbean Netherlands Cayman Islands Central African Republic Chad Channel Islands Chile China Hong Kong Sar China Macao Sar China Colombia Comoros Congo Cook Islands Costa Rica Cote D Ivoire Croatia Cuba Curacao Cyprus Czech Republic Democratic Republic Of The Congo Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Faeroe Islands Falkland Islands Malvinas Fiji Finland France French Guiana French Polynesia Gabon Gambia Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guatemala Guinea Bissau Guinea Guyana Haiti Holy See Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Isle Of Man Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kiribati Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Macedonia Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Martinique Mauritania Mauritius Mayotte Mexico Micronesia Moldova Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Palau Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Qatar Reunion Romania Russia Rwanda Saint Barthelemy Saint Helena Saint Kitts And Nevis Saint Lucia Saint Martin Saint Pierre And Miquelon Saint Vincent And The Grenadines Samoa San Marino Sao Tome And Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Sint Maarten Slovakia Slovenia Solomon Islands Somalia South Africa South Korea South Sudan Spain Sri Lanka State Of Palestine Sudan Suriname Swaziland Sweden Switzerland Syria Taiwan Tajikistan Tanzania Thailand Timor Leste Togo Tonga Trinidad And Tobago Tunisia Turkey Turks And Caicos Islands Uganda UK Ukraine United Arab Emirates Uruguay USA Uzbekistan Vanuatu Venezuela Viet Nam Wallis And Futuna Islands Western Sahara Yemen Zambia Zimbabwe

Select Date Range:

to

User Interface (UI): Body

The dashboard body contains output elements (plots).

dashboardBody(
  fluidRow(
    box(plotlyOutput("casesPlot"), width = 12),
    box(plotlyOutput("deathsPlot"), width = 12)
  )
)

Combine UI Components

All UI elements (header, sidebar, body) are combined into a dashboard layout.

ui <- dashboardPage(
  dashboardHeader(title = "COVID-19 Dashboard"),
  dashboardSidebar(
    selectInput("country", "Select Country:",
                choices = unique(data$country),
                selected = unique(data$country)[1]),
    
    dateRangeInput("dateRange",
                   "Select Date Range:",
                   start = min(data$date),
                   end = max(data$date))
  ),
  dashboardBody(
    fluidRow(
      box(plotlyOutput("casesPlot"), width = 12),
      box(plotlyOutput("deathsPlot"), width = 12)
    )
  )
)

Server: Data Filtering

The dataset is filtered dynamically based on user input.

filtered_data <- reactive({
  data %>%
    filter(country == input$country,
           date >= input$dateRange[1],
           date <= input$dateRange[2])
})

This ensures only relevant data is displayed.

Server Components

All server-side logic is combined inside the server function.

server <- function(input, output) {
  
  filtered_data <- reactive({
    data %>%
      filter(country == input$country,
             date >= input$dateRange[1],
             date <= input$dateRange[2])
  })
  
  output$casesPlot <- renderPlotly({
    p <- ggplot(filtered_data(), aes(x = date, y = daily_new_cases)) +
      geom_line(color = "blue") +
      labs(title = "Daily New Cases",
           x = "Date",
           y = "Cases")
    
    ggplotly(p)
  })
  
  output$deathsPlot <- renderPlotly({
    p <- ggplot(filtered_data(), aes(x = date, y = daily_new_deaths)) +
      geom_line(color = "red") +
      labs(title = "Daily New Deaths",
           x = "Date",
           y = "Deaths")
    
    ggplotly(p)
  })
}

Run the Application

The Shiny app is executed using the following command.

shinyApp(ui, server)

Shiny applications not supported in static R Markdown documents

Output:

This launches the interactive dashboard in a browser window.