Gain insights into using ggplot2 in R to create compelling visualizations. Learn about scatter plots, bar charts, customizing themes, and building interactive maps to enhance data storytelling.

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Data visualization in R using ggplot2 is an essential skill for data professionals and enthusiasts to efficiently discover and convey insights from datasets. Mastering ggplot2 allows you to uncover hidden patterns and trends in data, boosting decision-making and storytelling for a wide range of audiences. 

In this comprehensive course, you’ll begin by learning data visualization principles and the grammar of graphics. Progressing to ggplot2’s core functionalities, you’ll create scatter plots, bar charts, line graphs, histograms, and more explore advanced visualization through customizations and themes to create visually engaging plots. You’ll also be building interactive visualizations and captivating maps. 

By the end of this course, you’ll confidently generate engaging data visualizations in R, transforming yourself into an effective data communicator. You’ll also be able to elevate your data visualization skills with ggplot2 and excel as a data storyteller while enhancing your data science career.

Data Visualizations with ggplot2 in R

# What is the grammar of graphics?
First, let’s think about what a graphic is. How do we describe a graphic concisely, and can we build a representation of the description? The answers to these questions can help us understand the concepts involved in the grammar of graphics.

If we look at any graphic, we are likely to find a mapping of certain variables from the dataset to their visual representation in the graphic. The variables or data properties are typically numerical or categorical and are mapped visually as points (x and y coordinates), line colors, different markers, heights of bars, etc. 

We know that the grammar for a language is a set of rules describing the correct and acceptable usage of words. These words can be combined in a predefined, logical way, to form meaningful sentences. Similarly, graphics grammar offers principles for arranging mathematical and aesthetic aspects into a meaningful graph, implying that graphics are constructed on an underlying grammar.

There are two important principles here:

* Different layers of grammatical elements are used to create graphics.
* Plots are built with appropriate aesthetic mappings to make them plots meaningful.

In short, the grammar states that a statistical graphic is a mapping from data to aesthetic qualities (color, shape, and size) of geometric objects  (points, lines, bars). Additionally, the plot might include statistical data transformations depicted in a particular coordinate system.


Learn about the structured approach followed in the ggplot2 package with the grammar of graphics to build visualizations.

Welcome to the Course

Introduction to ggplot2

Drawing Basic Plots Using ggplot2

Advanced Plots

Plot Customization

Creating Panel of Plots

Building Interactive Plots

Uber Data Analysis Using the R Language

Summing Up

Appendix

Final Assessment

Stock Data Analysis with R

Grammar of Graphics in R

What is the grammar of graphics?