LA

Introduction

This presentation explains the development of an interactive COVID-19 dashboard using R Shiny.

The dashboard helps users explore COVID-19 data through visualizations and filters.

Objective

The main objective of this project is to:

• Analyze COVID-19 data
  
• Provide interactive data visualization
  
• Allow users to filter data easily
  
• Improve understanding of trends in cases and deaths

Tools and Technologies

The project uses the following tools:

• R Programming Language
  
• Shiny (for building interactive applications)
  
• Shinydashboard (for dashboard layout)
  
• ggplot2 (for data visualization)
  
• Plotly (for interactive graphs)
  
• dplyr (for data manipulation)

Dataset Description

The dataset contains COVID-19 information such as:

• Country names
  
• Dates
  
• Daily new cases
  
• Daily new deaths

This data is used to analyze trends over time.

Data Preprocessing

Before visualization, the data is prepared by:

• Loading the dataset
  
• Converting date column into proper format
  
• Ensuring consistency for filtering and plotting

This step is important for accurate results.

Dashboard Structure

The dashboard is divided into three main parts:

• Header: Displays the title
  
• Sidebar: Contains user inputs
  
• Body: Displays output graphs

This structure makes the application user-friendly.

User Inputs

The dashboard allows users to interact with data using:

• Country selection dropdown
  
• Date range selection

These inputs help users customize the data they want to view.

Data Filtering

Based on user inputs:

• The dataset is filtered dynamically
  
• Only selected country data is shown
  
• Data is restricted to chosen date range

This ensures relevant information is displayed.

Data Visualization

The dashboard provides two main visualizations:

• Daily New Cases (line graph)
  
• Daily New Deaths (line graph)

Graphs help in understanding trends clearly.

Interactivity

The dashboard is interactive because:

• Graphs update automatically when inputs change
  
• Users can hover, zoom, and explore data
  
• Visualization becomes more engaging and informative

Output

The final output is an interactive dashboard where users can:

• Select a country
  
• Choose a date range
  
• View trends in cases and deaths

Advantages

• Easy to use
  
• Provides real-time filtering
  
• Improves data understanding
  
• Interactive and visually appealing

Conclusion

The COVID-19 dashboard is a useful tool for analyzing pandemic data.

It demonstrates how interactive visualization can make complex data easier to understand.