Mastering ggplot2: From Novice to Data Viz Pro

Unleash Your Inner Data Scientist

Before We Start

In December 2017, after completing my first year of statistics, I delved into learning R. Having a background in Java, C, and C++ coding since high school, I enjoyed R but found its plots not so appealing and the code a bit tricky. On a quest for something beautiful and user-friendly, I stumbled upon a blog titled Beautiful plotting in R: A ggplot2 cheatsheet by Zev Ross, last updated in January 2016. Intrigued, I decided to follow the tutorial step by step, learning a great deal. As time passed, I tweaked and expanded the codes, adding new chart types and resources.

Realizing that Zev Ross’s blog hadn’t been updated for years, I took the initiative to create my own version, incorporating updates like the amazing {patchwork}, {ggtext}, and {ggforce} packages. I also shared insights on custom fonts, colors, and introduced a variety of R packages for interactive charts. The journey led to a unique tutorial, and now, I’ve decided to make it public, adding even more updates, such as Maps! because who doesn’t love maps!!

I incorporated the following enhancements into my tutorial:

• Following the R style guide (e.g., by Hadley Wickham, Google, or the Coding Club style guides).
• Implementing changes to the style and aesthetics of plots, including axis titles, legends, and color schemes for all plots.
• Ensuring that the tutorial remains up-to-date with changes in {ggplot2} (current version: 3.4.0).
• Modifying data import methods to utilize GitHub as a data source.
• Offering additional tips on various topics such as chart selection, color palettes, title modifications, adding lines, adjusting legends, annotations with labels, arrows and boxes, multi-panel plots, Geospatial Visualizations and interactive visualizations. …

What you’ll discover

• Tie Your Seatbelt: Setting the stage for your journey into advanced plotting techniques.
• The Dataset: Understanding the importance of data in crafting compelling visualizations.
• The {ggplot2} Package: Unleashing the power of {ggplot2} for elegant and customizable plots.
• A Default ggplot: Exploring the basics with a default {ggplot} and understanding its components.
• Working with Axes: Mastering the art of manipulating axes to convey meaningful insights.
• Working with Titles: Crafting informative and visually appealing titles to captivate your audience.
• Working with Legends: Enhancing clarity and interpretation by effectively managing legends.
• Working with Backgrounds & Grid Lines: Elevating aesthetics with stylish backgrounds and grid lines.
• Working with Margins: Fine-tuning margins to optimize plot presentation.
• Working with Multi-Panel Plots: Diving into the world of multi-panel plots for comprehensive data representation.
• Working with Colors: Harnessing the power of color to convey information and evoke emotions.
• Working with Themes: Creating cohesive visual narratives with carefully curated themes.
• Working with Lines: Adding emphasis and clarity through strategic use of lines.
• Working with Text: Utilizing text annotations to provide context and highlight key findings.
• Working with Coordinates: Manipulating coordinates to achieve desired plot layouts and perspectives.
• Working with Chart Types: Expanding your repertoire with diverse and impactful chart types.
• Working with Ribbons (AUC, CI, etc.): Enhancing visualizations with ribbons for confidence intervals and more.
• Working with Smoothings: Incorporating smoothings to reveal underlying trends and patterns.
• Working with Interactive Plots: Engaging your audience with interactive visualizations for dynamic exploration.
• Remarks, Tipps & Resources: Leveraging insights, tips, and resources to further refine your plotting skills.