R Programming A–Z 📊

🎉 Welcome to the R Programming A–Z repository!
This repository contains a collection of R scripts and projects to help you master R for data manipulation, visualization, and analytics.

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📚 What You Will Learn

• Core Programming Principles: Variables, loops, conditionals, and logical operations.
• R Fundamentals: Vectors, matrix operations, and functions.
• Data Frames: Importing, filtering, merging, and analyzing data.
• Advanced Visualization: Creating professional visualizations with ggplot2.
• Real-World Applications: Hands-on projects and exercises for practice.

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📂 Repository Structure

Section 1: Core Programming Principles 🧩

Learn the basics of R programming, including variables, loops, and logical operations.

Files:

• variables (S1).R — Introduction to variables.
• Logical_Values (S1).R — Working with logical values.
• LOOP(WHILE) (S1).R — Using while loops in R.
• Practice_with_Loops_While_and_for_(in) (S1).R — Loop exercises with while and for.
• Conditional_Statment_IF_Else_if_else_in_R (S1).R — Conditional statements: if-else.
• Workspace_Management_with_rm() in R (S1).R — Managing your workspace in R.
• Extra-rnorm() (S1).R — Using rnorm() for random number generation.

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Section 2: Fundamentals of R 🚀

Explore vectors, square brackets for subsetting, and functions in R.

Files:

• Vectors (S2).R — Creating and working with vectors.
• Vectorized_Operations_in_R (S2).R — Performing vectorized operations.
• Functions_in_R (S2).R — Defining and using functions in R.
• Advanced_Usage_of_[]_square_Brackets_in_R (S2).R — Subsetting data using [].
• Data_Visualization_with_ggplot2_in_R (S2).R — Introduction to ggplot2 visualization.
• The_Power_of_Vectorized_Operations_in_R (S2).R — Efficient data operations with vectors.

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Section 3: Matrices and Advanced Operations 🧮

Work with matrices, naming dimensions, and performing operations.

Files:

• Working_with_Matrices_in_R (S3).R — Creating and manipulating matrices.
• Naming_Dimensions_in_Matrices_and_Vectors (S3).R — Naming rows and columns.
• Advanced_Matrix_Operations_in_R (S3).R — Performing advanced operations with matrices.
• Subsetting_in_R (S3).R — Subsetting matrices and data.
• Basketball_Matrix_Operations (S3).R — Analyzing basketball data with matrices.
• s4-BasketballData (S3).R — Basketball matrix project data.

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Section 4: Data Frames and Analysis 📊

Learn to work with data frames for data analysis and manipulation.

Files:

• Basic_Operations_with_Data_Frames (S4).R — Performing operations on data frames.
• Filtering_Data_Frames_in_R (S4).R — Filtering rows in data frames.
• Building_Data_Frames_in_R (S4).R — Creating and building data frames.
• Merging_Data_Frames_in_R (S4).R — Merging and combining data frames.
• Data_Import_and_Exploration_in_R (S4).R — Importing and exploring datasets.
• CountryRegionVectors (S4).R — Handling country–region datasets.
• Demographic-Data (S4).R — Analyzing demographic data.
• Visualization_in_R_with_qplot() (S4).R — Creating quick plots using qplot().
• Advanced_Visualization_With_qplot_in_R (S4).R — Advanced customizations for qplot().

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Section 5: Advanced Visualization with ggplot2 📈

Master advanced visualization techniques using ggplot2.

Files:

• ggplot2 - Plotting_with_Layers_in_R (S5).R — Adding layers to ggplot visualizations.
• Histograms_and_Density_Charts_in_R (S5).R — Creating histograms and density charts.
• Mapping_vs_Setting_in_ggplot2 (S5).R — Understanding mapping vs. setting aesthetics.
• Overriding_Aesthetics_in_ggplot2 (S5).R — Customizing aesthetics in ggplot2.
• Perfecting_By_Adding_Themes_in_ggplot2 (S5).R — Adding themes for polished visuals.
• Layer_Creation (S5).R — Building layered visualizations step-by-step.
• Coordinates_in_R_ggplot2 (S5).R — Working with coordinate systems.
• Statistical_Transformations_in_R (S5).R — Adding statistical transformations to plots.
• Movie-Ratings (S5).R — Movie ratings visualization project.
• Section6-Grammar-Of-Graphics (S5).pdf — Documentation on the grammar of graphics.

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🚀 How to Use

1. Clone this repository to your local machine:

   git clone https://github.com/evgeniimatveev/R-Programming-A-Z.git
   cd R-Programming-A-Z

• Open the project in RStudio or your preferred IDE.

• Run the scripts section by section to practice and explore the concepts.

📧 Feedback

• If you have any suggestions, questions, or feedback, feel free to open an Issue.
• Let’s grow and learn together! 🚀

👨‍💻 Author

• Evgenii Matveev
• Data Analyst | R Programming Enthusiast