Chapter 1: Introduction to ggplot2
- Lesson 1: What is ggplot2?
- Lesson 2: History and Importance of ggplot2
- Lesson 3: Installing ggplot2 (Windows, macOS, Linux)
- Lesson 4: Understanding the Grammar of Graphics
- Lesson 5: Loading ggplot2 and Basic Plot Structure
Chapter 2: Basic Components of ggplot2
- Lesson 1: Understanding ggplot() and Aesthetics (aes())
- Lesson 2: Adding Geoms: Points, Lines, and Bars
- Lesson 3: Customizing Colors and Themes
- Lesson 4: Working with Labels and Titles
- Lesson 5: Adjusting Axis Labels and Legends
Chapter 3: Working with Geometries (Geoms)
- Lesson 1: Understanding geom_point() for Scatter Plots
- Lesson 2: Creating Line Graphs with geom_line()
- Lesson 3: Building Bar Charts with geom_bar()
- Lesson 4: Histograms and Density Plots
- Lesson 5: Boxplots and Violin Plots
Chapter 4: Customizing Plots with Themes and Scales
- Lesson 1: Using theme() for Styling ggplot2 Graphs
- Lesson 2: Changing Backgrounds and Grid Lines
- Lesson 3: Customizing Colors with scale_color_manual()
- Lesson 4: Adjusting Axis Scales (scale_x_continuous(), scale_y_continuous())
- Lesson 5: Using Prebuilt Themes (theme_minimal(), theme_dark())
Chapter 5: Faceting for Multiple Plots
- Lesson 1: Introduction to Faceting
- Lesson 2: Using facet_wrap() for Small Multiples
- Lesson 3: Using facet_grid() for Advanced Faceting
- Lesson 4: Adjusting Facet Labels and Layouts
- Lesson 5: When to Use Faceting vs Grouping
Chapter 6: Handling Data in ggplot2
- Lesson 1: Loading and Using Different Data Formats (csv, tsv, json)
- Lesson 2: Working with Tidy Data and the tidyverse
- Lesson 3: Grouping and Summarizing Data with dplyr
- Lesson 4: Filtering and Transforming Data Before Plotting
- Lesson 5: Reshaping Data for ggplot2 (pivot_longer() and pivot_wider())
Chapter 7: Adding Statistical Summaries
- Lesson 1: Using geom_smooth() for Trend Lines
- Lesson 2: Creating Mean and Median Lines
- Lesson 3: Working with Confidence Intervals
- Lesson 4: Using geom_boxplot() for Summary Statistics
- Lesson 5: Exploring Correlation with geom_smooth(method = "lm")
Chapter 8: Bar Charts and Categorical Data
- Lesson 1: Creating Simple Bar Charts
- Lesson 2: Grouped and Stacked Bar Charts
- Lesson 3: Using geom_col() for Custom Heights
- Lesson 4: Creating Diverging and Ordered Bar Charts
- Lesson 5: Using Colors Effectively for Categorical Data
Chapter 9: Scatter Plots and Line Charts
- Lesson 1: Basic Scatter Plot with geom_point()
- Lesson 2: Customizing Point Sizes and Colors
- Lesson 3: Line Charts with geom_line()
- Lesson 4: Combining Lines and Points (geom_line() + geom_point())
- Lesson 5: Best Practices for Time Series Data
Chapter 10: Histograms and Density Plots
- Lesson 1: Creating Histograms with geom_histogram()
- Lesson 2: Choosing Appropriate Bin Sizes
- Lesson 3: Overlaying Density Curves (geom_density())
- Lesson 4: Comparing Multiple Distributions
- Lesson 5: Log Scales and Transformations
Chapter 11: Saving and Exporting Plots
- Lesson 1: Using ggsave() for Saving Plots
- Lesson 2: Exporting to PNG, JPEG, PDF, and SVG
- Lesson 3: Adjusting Resolution and Size
- Lesson 4: Saving Multiple Plots with patchwork
- Lesson 5: Best Practices for High-Quality Graphics
Chapter 1: Advanced Geometries and Custom Layers
- Lesson 1: Working with geom_polygon() for Maps
- Lesson 2: Creating Waterfall Charts
- Lesson 3: Visualizing Networks with ggraph
- Lesson 4: Ridge Plots and Joy Plots
- Lesson 5: Customizing Geoms with Aesthetics
Chapter 2: Advanced Faceting and Small Multiples
- Lesson 1: Multi-layered Facets with facet_grid()
- Lesson 2: Controlling Scales in Faceted Plots
- Lesson 3: Arranging Multiple Plots with patchwork
- Lesson 4: Using gridExtra for Advanced Layouts
- Lesson 5: Creating Custom Grid Arrangements
Chapter 3: Annotating and Highlighting Data
- Lesson 1: Using geom_text() for Labels
- Lesson 2: Adding Annotations with annotate()
- Lesson 3: Highlighting Specific Data Points
- Lesson 4: Interactive Annotations with ggrepel
- Lesson 5: Best Practices for Readable Annotations
Chapter 4: Interactive Visualizations with ggplot2
- Lesson 1: Introduction to ggplotly for Interactivity
- Lesson 2: Creating Hover Effects and Tooltips
- Lesson 3: Building Interactive Dashboards with shiny
- Lesson 4: Animating Plots with gganimate
- Lesson 5: Exporting Interactive Graphics
Chapter 5: Advanced Statistical Visualizations
- Lesson 1: Time Series Analysis with geom_line()
- Lesson 2: Using geom_ribbon() for Confidence Bands
- Lesson 3: Creating Probability Distributions
- Lesson 4: Visualizing Regression Models
- Lesson 5: Advanced Boxplot Customization
Chapter 6: Customizing Color Scales
- Lesson 1: Using Color Palettes with scale_fill_manual()
- Lesson 2: Continuous Color Scales (scale_fill_gradient())
- Lesson 3: Diverging and Sequential Color Scales
- Lesson 4: Using RColorBrewer for Beautiful Palettes
- Lesson 5: Customizing Legends and Labels
Chapter 7: Handling Large Datasets with ggplot2
- Lesson 1: Efficiently Plotting Large Data
- Lesson 2: Using Binning and Aggregation for Performance
- Lesson 3: Sampling Strategies for Big Data
- Lesson 4: Working with Data Streaming
- Lesson 5: Performance Optimization Techniques
Chapter 8: Custom Themes and Publication-Ready Graphics
- Lesson 1: Creating Custom ggplot2 Themes
- Lesson 2: Best Practices for Journal Publications
- Lesson 3: Removing Backgrounds and Grid Lines
- Lesson 4: Choosing Fonts and Text Styles
- Lesson 5: ggplot2 for Business Reports
Chapter 9: Extending ggplot2 with Other Libraries
- Lesson 1: Integrating ggplot2 with ggmap for Maps
- Lesson 2: Using ggraph for Network Visualizations
- Lesson 3: Combining ggplot2 with plotly
- Lesson 4: Integrating ggplot2 with Shiny Dashboards
- Lesson 5: Extending ggplot2 with Custom Functions
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