Data Analysis in R

A comprehensive collection of R programming projects covering data manipulation, analysis, visualization, and web applications.

Project Structure

• 01-introduction-to-r/ - R programming fundamentals and basic operations
• 02-data-handling/ - Data manipulation and preprocessing techniques
• 03-data-cleaning/ - Data cleaning workflows and FIFA dataset analysis
• 04-data-visualization/ - COVID-19 data visualization and plotting techniques
• 05-text-mining/ - Text analysis including sentiment analysis and Twitter data
• 06-shiny-applications/ - Interactive web applications and dashboards
• documentation/ - Course materials and reference guides

Technologies Used

• R - Primary programming language
• R Markdown - Documentation and reporting
• Shiny - Interactive web applications
• ggplot2 - Data visualization
• dplyr - Data manipulation
• tidytext - Text mining and analysis

Featured Projects

• FIFA Data Analysis - Comprehensive analysis of FIFA World Cup data
• COVID-19 Dashboard - Interactive visualization of pandemic data
• Text Mining - Sentiment analysis of social media data
• NASA Fireball Dashboard - Shiny application for astronomical data

Getting Started

1. Clone the repository
2. Open the .Rproj file in RStudio
3. Install required packages: install.packages(c("shiny", "ggplot2", "dplyr", "tidytext"))
4. Navigate to any folder and open the .Rmd files

Skills Demonstrated

• Data cleaning and preprocessing
• Statistical analysis and modeling
• Data visualization and storytelling
• Interactive dashboard development
• Text mining and natural language processing
• Reproducible research with R Markdown