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Computer Science
Data Visualization
Data Visualization in R
1. Introduction to Data Visualization in R
2. Foundations of R for Data Visualization
3. Base R Graphics
4. The Grammar of Graphics with ggplot2
5. Common Plot Types with ggplot2
6. Advanced ggplot2 Techniques
7. Interactive and Dynamic Visualizations
8. Specialized Visualizations
9. Design Principles and Best Practices
10. Output and Sharing
The Grammar of Graphics with ggplot2
Core Components
Data Component
Data Frame Requirement
Tidy Data Structure
Aesthetic Mappings
aes() Function
Mapping Variables to Visuals
Global vs Local Aesthetics
Geometric Objects
geom Functions
Point Geometries
Line Geometries
Area Geometries
Text Geometries
Statistical Transformations
Built-in Statistics
stat Functions
Custom Statistics
Scales
Scale Functions
Continuous Scales
Discrete Scales
Color Scales
Position Scales
Coordinate Systems
Cartesian Coordinates
Polar Coordinates
Map Coordinates
Faceting
facet_wrap()
facet_grid()
Facet Customization
Themes
Built-in Themes
Theme Customization
Theme Elements
Building Plots Layer by Layer
Initializing with ggplot()
Data Specification
Global Aesthetics
Adding Layers
Geometric Layers
Statistical Layers
Annotation Layers
Layer Order and Interaction
Stacking Layers
Layer Inheritance
Aesthetic Mappings in Detail
Position Aesthetics
x and y Coordinates
Position Adjustments
Color and Fill
Color vs Fill
Continuous Color Mapping
Discrete Color Mapping
Size and Shape
Size Scaling
Shape Categories
Shape Customization
Alpha Transparency
Transparency Levels
Overplotting Solutions
Line Aesthetics
Line Types
Line Width
Grouping
Explicit Grouping
Implicit Grouping
Group Aesthetics
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5. Common Plot Types with ggplot2