Data Visualization in R
In data science, it’s not enough to be able to analyze data. You must also be able to create compelling visualizations to showcase your insights and help people understand your results.
In this introductory course on data visualization in R, you will learn about the different resources you can use to explore and showcase your data visually. Most importantly, you’ll learn how to use ggplot2, a powerful and immensely popular data visualization library for R.
By the end of this course, you will be able to create visualizations such as line charts, bar plots, scatter plots, histograms, and box plots to understand your data, and help others understand your data as well.
You will also learn how to add and work with multiple plots in your code to show different visualizations in a single dashboard.
At the end of the course, we’ll wrap up with a guided data science project. You will be able to combine all your new R data viz skills to create data visualizations that dig into real-world data about forest fires in Portugal to answer some interesting questions.
By the end of this course, you’ll be able to:
- Visualize changes over time using line graphs.
- Use histograms to understand data distributions.
- Compare graphs using bar charts and box plots.
- Understand relationships between variables using scatter plots.
Data Visualization in R Lessons List
Learn the basics of ggplot2 as you visualize change in life expectancy over time.
Learn techniques for visualizing variables using ggplot2.
Learn to visualize data distributions as you analyze movie reviews.
Learn to create and interpret scatter plots to explore relationships between variables.
Use data visualization techniques to explore data on forest fire occurrences.