Formatting ggplot2 Visualization Elements in R
Use the very popular ggplot2 visualization library and learn how to fine tune your charts. Special emphasis is put on color palettes, axes and scales, as well as plot themes.
Do you want to learn how to fine tune ggplots so that they look even better? Ggplots are great, but their fine tuning can be tricky. They work on different principles than standard R Base plots. So, there is a learning curve to this package. In this course, Formatting ggplot2 Visualization Elements in R, you will learn how ggplots are modified piece by piece. First, you will learn the general setup of a ggplot and how each ggplot has a typical logic that has to be followed. Next, you will discover how different color palettes can be used in ggplot2 and the several tools available that offer color palettes. You will be looking at these tools and how they are applied in a ggplot, including the R Color Brewer and Color Space. After that, you will be shown how the axes and scales of a plot are modified, as well as how to get access to each piece. Finally, you will have the skills to modify the plot theme, which leads to the component of a ggplot that defines its appearance. When you are finished with this course, you will better understand the logic behind ggplot2 and you will be able to modify the plot theme, the axes, and the coloration.
Author Name: Martin Burger
Author Description:
Martin studied biostatistics and worked for several pharmaceutical companies before he became a data science consultant and author. He published over 15 courses on R, Tableau 9 and other data science related subjects. His main focus lies on analytics software like R and SPSS but he is also interested in modern data visualization tools like Tableau. If he is not busy coding, blogging or working out new teaching concepts you may find him skiing or hiking in the Alps.
Table of Contents
- Course Overview
1min - Understanding a ggplot2 Setup
39mins - Changing Default Color Settings
22mins - Working on Plot Axes
33mins - Using and Changing Plot Themes in ggplot2
23mins
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