Data Visualization in R and Python

Table of Contents

1. Cover
2. Table of Contents
3. Title Page
4. Copyright
5. Preface
6. Introduction
7. About the Companion Website
8. Part I: Static Graphics with ggplot (R) and Seaborn (Python)
   1. 1 Scatterplots and Line Plots
      1. 1.1 R: ggplot
      2. 1.2 Python: Seaborn
   2. 2 Bar Plots
      1. 2.1 R: ggplot
      2. 2.2 Python: Seaborn
   3. 3 Facets
      1. 3.1 R: ggplot
      2. 3.2 Python: Seaborn
   4. 4 Histograms and Kernel Density Plots
      1. 4.1 R: ggplot
      2. 4.2 Python: Seaborn
   5. 5 Diverging Bar Plots and Lollipop Plots
      1. 5.1 R: ggplot
      2. 5.2 Python: Seaborn
   6. 6 Boxplots
      1. 6.1 R: ggplot
      2. 6.2 Python: Seaborn
   7. 7 Violin Plots
      1. 7.1 R: ggplot
      2. 7.2 Python: Seaborn
   8. 8 Overplotting, Jitter, and Sina Plots
      1. 8.1 Overplotting
      2. 8.2 R: ggplot
      3. 8.3 Python: Seaborn
   9. 9 Half-Violin Plots
      1. 9.1 R: ggplot
      2. 9.2 Python: Seaborn
   10. 10 Ridgeline Plots
       1. 10.1 History of the Ridgeline
       2. 10.2 R: ggplot
   11. 11 Heatmaps
       1. 11.1 R: ggplot
       2. 11.2 Python: Seaborn
   12. 12 Marginals and Plots Alignment
       1. 12.1 R: ggplot
       2. 12.2 Python: Seaborn
   13. 13 Correlation Graphics and Cluster Maps
       1. 13.1 R: ggplot
       2. 13.2 Python: Seaborn
       3. 13.3 R: ggplot
       4. 13.4 Python: Seaborn
9. Part II: Interactive Graphics with Altair
   1. 14 Altair Interactive Plots
      1. 14.1 Scatterplots
      2. 14.2 Line Plots
      3. 14.3 Bar Plots
      4. 14.4 Bubble Plots
      5. 14.5 Heatmaps and Histograms
10. Part III: Web Dashboards
    1. 15 Shiny Dashboards
       1. 15.1 General Organization
       2. 15.2 Second Version: Graphics and Style Options
       3. 15.3 Third Version: Tabs, Widgets, and Advanced Themes ...