Data visualisation is a critical skill for anyone who regularly uses quantitative data in their work, which means that data visualisation is a tool that almost every worker today requires. The R statistical Data Visualization in R language is a critical tool for data visualisation today. R has evolved into an extremely powerful and flexible platform for creating figures, tables, and reproducible reports, especially when combined with the tidyverse software packages. However, R can be intimidating for first-time users, and there are so many resources available online that it can be difficult to navigate without assistance.
This is the second course in Johns Hopkins’ Data Visualization specialization. It is designed for students who have prior experience with R and data manipulation in the tidyverse, or who have completed the previous course in the specialization. This course focuses on learning to use ggplot2 to create a variety of visualisations and polish those visualisations using ggplot tools as well as vector graphics editing software. The course will not go into specifics about how data management works in the background.
ggplot2 is an R package for data visualization. It can significantly improve the quality and aesthetics of your graphics while also making you much more efficient in their creation.
ggplot2 can create almost any type of chart. Because the R graph gallery focuses on it, almost every section begins with ggplot2 examples.
This page contains general ggplot2 tips that can be applied to any chart, such as customising a title, adding annotation, or using faceting.
A human can easily obtain information about hidden patterns in data that may be overlooked by using visualisation techniques.
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